Multi-subframe quantization of spectral parameters

Abstract

Speech is encoded into a frame of bits. A speech signal is digitized into a sequence of digital speech samples that are then divided into a sequence of subframes. A set of model parameters is estimated for each subframe. The model parameters include a set of spectral magnitude parameters that represent spectral information for the subframe. Two or more consecutive subframes from the sequence of subframes may be combined into a frame. The spectral magnitude parameters from both of the subframes within the frame may be jointly quantized. The joint quantization includes forming predicted spectral magnitude parameters from the quantized spectral magnitude parameters from the previous frame, computing the residual parameters as the difference between the spectral magnitude parameters and the predicted spectral magnitude parameters, combining the residual parameters from both of the subframes within the frame, and quantizing the combined residual parameters into a set of encoded spectral bits which are included in the frame of bits.

Description

BACKGROUND

The invention is directed to encoding and decoding speech.

Speech encoding and decoding have a large number of applications and have been studied extensively. In general, one type of speech coding, referred to as speech compression, seeks to reduce the data rate needed to represent a speech signal without substantially reducing the quality or intelligibility of the speech. Speech compression techniques may be implemented by a speech coder.

A speech coder is generally viewed as including an encoder and a decoder. The encoder produces a compressed stream of bits from a digital representation of speech, such as may be generated by converting an analog signal produced by a microphone using an analog-to-digital converter. The decoder converts the compressed bit stream into a digital representation of speech that is suitable for playback through a digital-to-analog converter and a speaker. In many applications, the encoder and decoder are physically separated, and the bit stream is transmitted between them using a communication channel.

A key parameter of a speech coder is the amount of compression the coder achieves, which is measured by the bit rate of the stream of bits produced by the encoder. The bit rate of the encoder is generally a function of the desired fidelity (i.e., speech quality) and the type of speech coder employed. Different types of speech coders have been designed to operate at high rates (greater than 8 kbs), mid-rates (3-8 kbs) and low rates (less than 3 kbs). Recently, mid-rate and low-rate speech coders have received attention with respect to a wide range of mobile communication applications (e.g., cellular telephony, satellite telephony, land mobile radio, and in-flight telephony). These applications typically require high quality speech and robustness to artifacts caused by acoustic noise and channel noise (e.g., bit errors).

Vocoders are a class of speech coders that have been shown to be highly applicable to mobile communications. A vocoder models speech as the response of a system to excitation over short time intervals. Examples of vocoder systems include linear prediction vocoders, homomorphic vocoders, channel vocoders, sinusoidal transform coders ("STC"), multiband excitation ("MBE") vocoders, and improved multiband excitation ("IMBE.TM.") vocoders. In these vocoders, speech is divided into short segments (typically 10-40 ms) with each segment being characterized by a set of model parameters. These parameters typically represent a few basic elements of each speech segment, such as the segment's pitch, voicing state, and spectral envelope. A vocoder may use one of a number of known representations for each of these parameters. For example the pitch may be represented as a pitch period, a fundamental frequency, or a long-term prediction delay. Similarly the voicing state may be represented by one or more voiced/unvoiced decisions, by a voicing probability measure, or by a ratio of periodic to stochastic energy. The spectral envelope is often represented by an all-pole filter response, but also may be represented by a set of spectral magnitudes or other spectral measurements.

Since they permit a speech segment to be represented using only a small number of parameters, model-based speech coders, such as vocoders, typically are able to operate at medium to low data rates. However, the quality of a model-based system is dependent on the accuracy of the underlying model. Accordingly, a high fidelity model must be used if these speech coders are to achieve high speech quality.

One speech model which has been shown to provide high quality speech and to work well at medium to low bit rates is the Multi-Band Excitation (MBE) speech model developed by Griffin and Lim. This model uses a flexible voicing structure that allows it to produce more natural sounding speech, and which makes it more robust to the presence of acoustic background noise. These properties have caused the MBE speech model to be employed in a number of commercial mobile communication applications.

The MBE speech model represents segments of speech using a fundamental frequency, a set of binary voiced/unvoiced (V/UV) metrics, and a set of spectral magnitudes. A primary advantage of the MBE model over more traditional models is in the voicing representation. The MBE model generalizes the traditional single V/UV decision per segment into a set of decisions, each representing the voicing state within a particular frequency band. This added flexibility in the voicing model allows the MBE model to better accommodate mixed voicing sounds, such as some voiced fricatives. In addition this added flexibility allows a more accurate representation of speech that has been corrupted by acoustic background noise. Extensive testing has shown that this generalization results in improved voice quality and intelligibility.

The encoder of an MBE-based speech coder estimates the set of model parameters for each speech segment. The MBE model parameters include a fundamental frequency (the reciprocal of the pitch period); a set of V/UV metrics or decisions that characterize the voicing state; and a set of spectral magnitudes that characterize the spectral envelope. After estimating the MBE model parameters for each segment, the encoder quantizes the parameters to produce a frame of bits. The encoder optionally may protect these bits with error correction/detection codes before interleaving and transmitting the resulting bit stream to a corresponding decoder.

The decoder converts the received bit stream back into individual frames. As part of this conversion, the decoder may perform deinterleaving and error control decoding to correct or detect bit errors. The decoder then uses the frames of bits to reconstruct the MBE model parameters, which the decoder uses to synthesize a speech signal that perceptually resembles the original speech to a high degree. The decoder may synthesize separate voiced and unvoiced components, and then may add the voiced and unvoiced components to produce the final speech signal.

In MBE-based systems, the encoder uses a spectral magnitude to represent the spectral envelope at each harmonic of the estimated fundamental frequency. Typically each harmonic is labeled as being either voiced or unvoiced, depending upon whether the frequency band containing the corresponding harmonic has been declared voiced or unvoiced. The encoder then estimates a spectral magnitude for each harmonic frequency. When a harmonic frequency has been labeled as being voiced, the encoder may use a magnitude estimator that differs from the magnitude estimator used when a harmonic frequency has been labeled as being unvoiced. At the decoder, the voiced and unvoiced harmonics are identified, and separate voiced and unvoiced components are synthesized using different procedures. The unvoiced component may be synthesized using a weighted overlap-add method to filter a white noise signal. The filter is set to zero all frequency regions declared voiced while otherwise matching the spectral magnitudes labeled unvoiced. The voiced component is synthesized using a tuned oscillator bank, with one oscillator assigned to each harmonic that has been labeled as being voiced. The instantaneous amplitude, frequency and phase are interpolated to match the corresponding parameters at neighboring segments.

MBE-based speech coders include the IMBE.TM. speech coder and the AMBE.RTM. speech coder. The AMBE.RTM. speech coder was developed as an improvement on earlier MBE-based techniques. It includes a more robust method of estimating the excitation parameters (fundamental frequency and V/UV decisions) which is better able to track the variations and noise found in actual speech. The AMBE.RTM. speech coder uses a filterbank that typically includes sixteen channels and a non-linearity to produce a set of channel outputs from which the excitation parameters can be reliably estimated. The channel outputs are combined and processed to estimate the fundamental frequency and then the channels within each of several (e.g., eight) voicing bands are processed to estimate a V/UV decision (or other voicing metric) for each voicing band.

The AMBE.RTM. speech coder also may estimate the spectral magnitudes independently of the voicing decisions. To do this, the speech coder computes a fast Fourier transform ("FFT") for each windowed subframe of speech and then averages the energy over frequency regions that are multiples of the estimated fundamental frequency. This approach may further include compensation to remove from the estimated spectral magnitudes artifacts introduced by the FFT sampling grid.

The AMBE.RTM. speech coder also may include a phase synthesis component that regenerates the phase information used in the synthesis of voiced speech without explicitly transmitting the phase information from the encoder to the decoder. Random phase synthesis based upon the V/UV decisions may be applied, as in the case of the IMBE.TM. speech coder. Alternatively, the decoder may apply a smoothing kernel to the reconstructed spectral magnitudes to produce phase information that may be perceptually closer to that of the original speech than is the randomly-produced phase information.

The techniques noted above are described, for example, in Flanagan, Speech Analysis, Synthesis and Perception, Springer-Verlag, 1972, pages 378-386 (describing a frequency-based speech analysis-synthesis system); Jayant et al., Digital Coding of Waveforms, Prentice-Hall, 1984 (describing speech coding in general); U.S. Pat. No. 4,885,790 (describing a sinusoidal processing method); U.S. Pat. No. 5,054,072 (describing a sinusoidal coding method); Almeida et al., "Nonstationary Modeling of Voiced Speech", IEEE TASSP, Vol. ASSP-31, No. 3, June 1983, pages 664-677 (describing harmonic modeling and an associated coder); Almeida et al., "Variable-Frequency Synthesis: An Improved Harmonic Coding Scheme", IEEE Proc. ICASSP 84, pages 27.5.1-27.5.4 (describing a polynomial voiced synthesis method); Quatieri et al., "Speech Transformations Based on a Sinusoidal Representation", IEEE TASSP, Vol, ASSP34, No. 6, Dec. 1986, pages 1449-1986 (describing an analysis-synthesis technique based on a sinusoidal representation); McAulay et al., "Mid-Rate Coding Based on a Sinusoidal Representation of Speech", Proc. ICASSP 85, pages 945-948, Tampa, Fla., March 26-29, 1985 (describing a sinusoidal transform speech coder); Griffin, "Multiband Excitation Vocoder", Ph.D. Thesis, M.I.T, 1987 (describing the Multi-Band Excitation (MBE) speech model and an 8000 bps MBE speech coder); Hardwick, "A 4.8 kbps Multi-Band Excitation Speech Coder", SM. Thesis, M.I.T, May 1988 (describing a 4800 bps Multi-Band Excitation speech coder); Telecommunications Industry Association (TIA), "APCO Project 25 Vocoder Description", Version 1.3, Jul. 15, 1993, IS102BABA (describing a 7.2 kbps IMBE.TM. speech coder for APCO Project 25 standard); U.S. Pat. No. 5,081,681 (describing IMBE.TM. random phase synthesis); U.S. Pat. No. 5,247,579 (describing a channel error mitigation method and format enhancement method for MBE-based speech coders); U.S. Pat. No. 5,226,084 (describing quantization and error mitigation methods for MBE-based speech coders); U.S. Pat. No. 5,517,511 (describing bit prioritization and FEC error control methods for MBE-based speech coders).

SUMMARY

The invention features a new AMBE.RTM. speech coder for use, for example, in a wireless communication system to produce high quality speech from a bit stream transmitted across a wireless communication channel at a low data rate. The speech coder combines low data rate, high voice quality, and robustness to background noise and channel errors. This promises to advance the state of the art in speech coding for mobile communications. The new speech coder achieves high performance through a new multi-subframe spectral magnitude quantizer that jointly quantizes spectral magnitudes estimated from two or more consecutive subframes. The quantizer achieves fidelity comparable to prior art systems while using fewer bits to quantize the spectral magnitude parameters. AMBE.RTM. speech coders are described generally in U.S. application Ser. No. 08/222,119, filed Apr. 4, 1994 and entitled "ESTIMATION OF EXCITATION PARAMETERS"; U.S. application Ser. No. 08/392,188, filed Feb. 22, 1995 and entitled "SPECTRAL REPRESENTATIONS FOR MULTI-BAND EXCITATION SPEECH CODERS"; and U.S. Application No. 08/392,099, filed Feb. 22, 1995 and entitled "SYNTHESIS OF SPEECH USING REGENERATED PHASE INFORMATION", all of which are incorporated by reference.

In one aspect, generally, the invention features encoding speech into a frame of bits. A speech signal is digitized into a sequence of digital speech samples that are divided into a sequence of subframes, each of which includes multiple digital speech samples. A set of speech model parameters is estimated for each subframe, the parameters including a set of spectral magnitude parameters that represent spectral information for the subframe. Consecutive subframes then are combined into a frame, and the spectral magnitude parameters from the subframes of the frame are jointly quantized to produce a set of encoder spectral bits that are included in a frame of bits for transmission or storage. The joint quantization includes forming predicted spectral magnitude parameters from quantized spectral magnitude parameters from a previous frame.

Embodiments of the invention may include one or more of the following features. The joint quantization may include computing residual parameters as the difference between the spectral magnitude parameters and the predicted spectral magnitude parameters. The residual parameters from the subframes of the frame may be combined and quantized into a set of encoder spectral bits.

The residual parameters may be combined by dividing the residual parameters from each subframe into frequency blocks and performing a linear transformation on the residual parameters within each frequency block to produce a set of transformed residual coefficients for each subframe. A minority of the transformed residual coefficients from the frequency blocks for each subframe may be grouped into a PRBA vector for the subframe, and the remaining transformed residual coefficients for each frequency block of each subframe may be grouped into a higher order coefficient (HOC) vector for the frequency block. The prediction residual block average (PRBA) vectors may be transformed to produce a transformed PRBA vector for each subframe, and the transformed PRBA vectors for the subframes of the frame may be combined by computing generalized sum and difference vectors from the transformed PRBA vectors, and combining the HOC vectors within each frequency block for the subframes of the frame by computing generalized sum and difference vectors from the HOC vectors for each frequency block.

The predicted spectral magnitude parameters may be formed by applying a gain of less than unity to a linear interpolation of quantized spectral magnitudes from a last subframe in a previous frame. The transformed residual coefficients may be computed for each frequency block using a Discrete Cosine Transform (DCT) followed by a linear two by two transform on two lowest order DCT coefficients. The length of each frequency block may be approximately proportional to a number of spectral magnitude parameters within the subframe.

The combined residual parameters may be quantized using a vector quantizer. Vector quantization may be applied to all or part of the generalized sum and difference vectors computed from the transformed PRBA vectors, and may be applied to all or part of the generalized sum and difference vectors computed from the HOC vectors.

Additional encoder bits may be produced by quantizing additional speech model parameters other than the spectral magnitude parameters. The additional speech model parameters may include parameters representative of a fundamental frequency and parameters representative of a voicing state. The frame of bits also may include redundant error control bits that protect at least some of the encoder spectral bits. The spectral magnitude parameters may represent log spectral magnitudes estimated for a Multi-Band Excitation (MBE) speech model, and may be estimated from a computed spectrum in a manner which is independent of a voicing state.

In another aspect, generally, the invention features decoding speech from a frame of bits. Decoder spectral bits are extracted from the frame of bits, and are used to jointly reconstruct spectral magnitude parameters for consecutive subframes within a frame of speech. The joint reconstruction includes inverse quantizing the decoder spectral bits to reconstruct a set of combined residual parameters for the frame from which separate residual parameters for each of the subframes are computed. Predicted spectral magnitude parameters are formed from reconstructed spectral magnitude parameters from a previous frame. The separate residual parameters are added to the predicted spectral magnitude parameters to form the reconstructed spectral magnitude parameters for each subframe within the frame. Digital speech samples are synthesized for each subframe using speech model parameters that include some or all of the reconstructed spectral magnitude parameters for the subframe.

Embodiments of this aspect of the invention may include one or more of the following features. The separate residual parameters may be computed by dividing each subframe into frequency blocks. The combined residual parameters for the frame may be separated into generalized sum and difference vectors representing transformed PRBA vectors combined across the subframes of the frame, and into generalized sum and difference vectors representing HOC vectors for the frequency blocks combined across the subframes of the frame. PRBA vectors may be computed for each subframe from the generalized sum and difference vectors representing the transformed PRBA vectors. HOC vectors may be computed for each subframe from the generalized sum and difference vectors representing the HOC vectors for each of the frequency blocks. The PRBA vector and the HOC vectors for each of the frequency blocks may be combined to form transformed residual coefficients for each of the subframes, and an inverse transformation may be performed on the transformed residual coefficients to produce the separate residual parameters for each subframe of the frame.

The predicted spectral magnitude parameters may be formed by applying a gain of less than unity to a linear interpolation of quantized spectral magnitudes from a last subframe of a previous frame. The separate residual parameters may be computed from the transformed residual coefficients by performing on each of the frequency blocks an inverse linear two by two transform on the two lowest order transformed residual coefficients within the frequency block and then performing an Inverse Discrete Cosine Transform (IDCT) over all the transformed residual coefficients within the frequency block.

Four of the frequency blocks may be used per subframe, and the length of each frequency block may be approximately proportional to a number of spectral magnitude parameters within the subframe. Inverse quantization to reconstruct a set of combined residual parameters for the frame may include using inverse vector quantization applied to one or more vectors.

The frame of bits may include other decoder bits in addition to the decoder spectral bits. These bits may be representative of speech model parameters other than the spectral magnitude parameters, such as a fundamental frequency and parameters representative of a voicing state. The frame of bits also may include redundant error control bits protecting at least some of the decoder spectral bits.

The reconstructed spectral magnitude parameters may represent log spectral magnitudes used in a Multi-Band Excitation (MBE) speech model. Synthesizing of speech for each subframe may include computing a set of phase parameters from the reconstructed spectral magnitude parameters.

In another aspect, the invention features encoding a level of speech into a frame of bits by digitizing a speech signal into a sequence of digital speech samples and dividing the digital speech samples into a sequence of subframes that each include multiple digital speech samples. A speech level parameter is estimated for each subframe. The speech level parameter is representative of the amplitude of the digital speech samples of the subframe. Consecutive subframes are combined into a frame, and the speech level parameters from the subframes within the frame are jointly quantized. This quantization includes computing and quantizing an average level parameter by combining the speech level parameters over the subframes within the frame, and computing and quantizing a difference level vector between the speech level parameters for each subframe within the frame and the average level parameter. Quantized bits representative of the average level parameter and the difference level vector are included in a frame of bits.

Embodiments of this aspect of the invention may include one or more of the following features. The speech level parameter for each subframe may be estimated as a mean of a set of spectral magnitude parameters computed for each subframe plus an offset. The spectral magnitude parameters may represent log spectral magnitudes estimated for a Multi-Band Excitation (MBE) speech model. The offset may be dependent on a number of spectral magnitude parameters in the frame.

The difference level vector may be quantized using vector quantization, and the frame of bits may include error control bits used to protect some or all of the quantized bits representative of the average level parameter and the difference level vector.

Other features and advantages of the invention will be apparent from the following description, including the drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a simplified block diagram of a wireless communications system.

FIG. 2 is a block diagram of a communication link of the system of FIG. 1.

FIGS. 3 and 4 are block diagrams of an encoder and a decoder of the system of FIG. 1.

FIG. 5 is a general block diagram of components of the encoder of FIG. 3.

FIG. 6 is a flowchart of voice and tone detection functions of the encoder.

FIG. 7 is a block diagram of a multi-subframe magnitude quantizer of the encoder of FIG. 5.

FIG. 8 is a block diagram of a mean vector quantizer of the magnitude quantizer of FIG. 7.

DESCRIPTION

An embodiment of the invention is described in the context of a new AMBE.RTM. speech coder, or vocoder, which is widely applicable to the problems of wireless communications such as cellular or satellite telephony, mobile radio, airphones, voice pagers, and digital storage of speech such as in telephone answering machines and dictation equipment. Referring to FIG. 1, a mobile terminal or telephone 40 is connected across a wireless communication channel 42 to a mobile gateway or base station 44 which is connected to the public switched telephone network (PSTN) 46. The speech coder in the mobile telephone 40 and in the mobile base station 44 allows conventional telephones 48 to be bridged into the wireless network.

The described vocoder has a 40 ms frame size and operates at a data rate of 3900 bps (156 bits per frame). These bits are divided between speech coding and forward error control ("FEC") coding to increase the robustness of the system to bit errors that normally occur across a wireless communication channel. The vocoder is designed to operate most efficiently at low to medium data rates in which speech is coded and transmitted at rates of 1500 bps to 8000 bps, ignoring bits associated with FEC coding. However, appropriate modifications can be made to the vocoder to enable it to work at other data rates. The vocoder also may be adapted to other frame sizes, such as, for example, 30-60 ms frames. In one implementation, a dual-rate embodiment using a 45 ms frame size has been operated at data rates of 3467 bps and 6933 bps.

Referring to FIG. 2, the mobile telephone at the transmitting end achieves voice communication by digitizing speech 50 received through a microphone 60 using an analog-to-digital (A/D) converter 70 that samples the speech at a frequency of 8 kHz. The digitized speech signal passes through a speech encoder 80, where it is processed as described below. The signal is then transmitted across the communication link by a transmitter 90. At the other end of the communication link, a receiver 100 receives the signal and passes it to a decoder 110. The decoder converts the signal into a synthetic digital speech signal. A digital-to-analog (D/A) converter 120 then converts the synthetic digital speech signal into an analog speech signal that is converted into audible speech 140 by a speaker 130.

The speech coder in each terminal includes an encoder 80 and a decoder 110. As shown in FIG. 3, the encoder includes three main functional blocks: speech analysis 200, parameter quantization 210, and FEC encoding 220. FEC encoding typically includes bit prioritization and interleaving. As shown in FIG. 4, the decoder is similarly divided into FEC decoding 230, which may include deinterleaving and inverse bit prioritization, parameter reconstruction 240 (i.e., inverse quantization) and speech synthesis 250.

The speech coder may be designed to operate at multiple data rates. However, the described embodiment is a 3900 bps vocoder using 156 bits per 40 ms frame. These bits are divided into 103 bits used for the voice (i.e. source) coding plus 53 bits used for forward error correction (FEC) coding. Each 40 ms frame is divided into two 20 ms subframes, and speech analysis and synthesis are performed on a subframe basis while quantization and FEC coding are performed on a frame basis.

The FEC typically includes one or more short block codes and/or convolution codes. In the described embodiment, one [24,12] extended Golay code, three [23,12] Golay codes and two [15,11] Hamming codes are employed for each frame. The codes possessing more redundancy (i.e., the Golay codes) are used on the most sensitive voice bits while the codes with less redundancy (i.e., the Hamming codes) are used on less sensitive voice bits and the least sensitive voice bits are not protected with any code.

The data rate may be varied by changing either the number of voice bits or the number of FEC bits. There is a gradual effect on performance as the data rate is changed. Changes in the number of voice bits may be accommodated by reallocating the number of bits used to quantize the model parameters. In the event of a significantly higher data rate, where a corresponding increase in the number of bits used for vector quantization of the magnitude parameters would result in excessive complexity, scalar quantization, or a hierarchical approach that combines vector quantization as featured in the described embodiment with an error quantizer that quantizes the difference between the unquantized spectral magnitudes and the reconstructed result from vector quantization, may be used. An error quantizer using scalar quantization has been implemented in the context of a dual-rate system. The error quantizer reduces quantization distortion and increases perceived quality while adding only minimal complexity.

Referring to FIG. 3, the encoder first performs speech analysis 200. The first step in speech analysis is filterbank processing on each subframe followed by estimation of the MBE model parameters for each subframe. This involves dividing the input signal into overlapping subframes using an analysis window. For each 20 ms subframe, a MBE subframe parameter estimator estimates a set of model parameters that include a fundamental frequency (inverse of the pitch period), a set of voiced/unvoiced (V/UV) metrics and a set of spectral magnitudes. These parameters are generated using AMBE techniques. The speech parameters fully describe the speech signal and are passed to the encoder's quantization 210 block for further processing. Speech analysis techniques for AMBE.RTM. speech coders are described generally in U.S. Application No. 08/222,119, filed Apr. 4, 1994 and entitled "ESTIMATION OF EXCITATION PARAMETERS"; U.S. Application No. 08/392,188, filed Feb. 22, 1995 and entitled "SPECTRAL REPRESENTATIONS FOR MULTI-BAND EXCITATION SPEECH CODERS"; and U.S. Application No. 08/392,099, filed Feb. 22, 1995 and entitled "SYNTHESIS OF SPEECH USING REGENERATED PHASE INFORMATION", all of which are incorporated by reference.

Referring to FIG. 5, once the subframe model parameters 500 and 505 are estimated for the two subframes of a frame, a fundamental frequency quantizer 510 receives the estimated fundamental frequency parameters from both subframes, quantizes these parameters, and produces a set of bits encoding the fundamental frequencies for both subframes. A voicing quantizer 515 receives estimated voicing metrics for both subframes, and then quantizes these parameters into a set of encoded bits representing the voicing state within the frame. The encoded fundamental frequency bits and voicing bits are fed to a combiner 520 along with encoded spectral bits from a multi-subframe spectral magnitude quantizer 525. FEC encoding 530 is applied to the output of the combiner 520 and the resulting frame of bits 535 is suitable for transmission or storage.

As shown in FIG. 6, the encoder may incorporate an adaptive Voice Activity Detector (VAD) that classifies each subframe as either voice, background noise or a tone according to a procedure 600. The VAD algorithm uses local information to distinguish voice subframes from background noise (step 605). If both subframes within a frame are classified as noise (step 610), then the encoder quantizes the background noise that is present as a special Noise frame (step 615). When a frame is a noise frame, the system may choose not to transmit the frame to the decoder and the decoder will use previously received noise data in place of the missing frame. This voice activated transmission technique increases performance of the system by only requiring voice frames and occasional noise frames to be transmitted.

The encoder also may feature tone detection and transmission in support of DTMF, call progress (e.g., dial, busy and ringback) and single tones. The encoder checks each subframe to determine whether the current subframe contains a valid tone signal. If a tone is detected in a subframe (step 620), then the encoder quantizes the detected tone parameters (magnitude and index) in a special Tone frame as shown in Table 1 (step 625) and applies FEC coding prior to transmitting the frame to the decoder for subsequent synthesis. If a tone is not detected, then a standard voice frame is quantized as described below (step 630).

TABLE 1______________________________________Tone Frame Bit Representationb [ ]element # Value______________________________________0-3 154-9 1610-12 3 MSB's of Amplitude13-14 015-19 5 LSB's of Amplitude20-27 Detected Tone Index28-35 Detected Tone Index36-43 Detected Tone Index. .. .84-91 Detected Tone Index92-99 Detected Tone Index100-102 0______________________________________

The vocoder includes VAD and Tone detection to classify each frame as either a standard Voice frame, a special Tone frame, or a special Noise frame. In the event that a frame is not classified as a special Tone frame, then the voice or noise information (as determined by the VAD) is quantized for the pair of subframes. The 156 available bits are allocated over the model parameters and FEC coding as shown in Table 2. After reserving bits for the excitation parameters (fundamental frequency and voicing metrics) and FEC coding, there are 85 bits available for the spectral magnitudes.

TABLE 2______________________________________Bit Allocation for Voice or Noise FramesVocoderParameter Bits______________________________________Fund. Freq. 10Voicing Metrics 8Gain 5 + 5 = 10PRBA Vector 8 + 6 + 7 + 8 + 6 = 35HOC Vector 4*(7 + 3) = 40FEC Coding 12 + 3*11 + 2*4 = 53Total 156______________________________________

The multi-subframe quantizer quantizes the spectral magnitudes. The quantizer combines logarithmic companding, spectral prediction, discrete cosine transforms (DCTs) and vector and scalar quantization to achieve high efficiency, measured in terms of fidelity per bit, with reasonable complexity. The quantizer can be viewed as a two-dimensional (time-frequency) predictive transform coder. The quantizer jointly encodes the spectral magnitudes from all of the subframes (typically two) of the current frame. As a first step, the quantizer computes the logarithm of the estimated spectral magnitudes for each subframe to convert them into a domain that is better for quantization. The quantizer then may apply a low-frequency boost to the log spectral magnitudes to compensate for missing low-frequency energy which may have been removed through filtering in the telephone system or elsewhere. The magnitude quantizer then computes predicted spectral parameters for each subframe using quantized and reconstructed log spectral magnitudes from the last subframe of the prior frame. These prior magnitudes are linearly interpolated and resampled to compensate for the possible difference between the number of magnitudes in the prior subframe and the number of magnitudes in each of the subframes in the current frame. In addition to interpolation and resampling, the computation of the predicted spectral parameters removes the mean value of the parameters and applies a multiplicative "leakage factor" that is less than one (e.g., 0.8) to ensure that any error in previous magnitudes caused by bit errors decays away over a few frames.

FIG. 7 illustrates a dual-frame magnitude quantizer that receives inputs 1a and 1b from the MBE parameter estimators for two consecutive subframes. Input 1a represents the spectral magnitudes for odd numbered subframes and is given an index of 1. The number of magnitudes for subframe number 1 is designated by L.sub.1. Input 1b represents the spectral magnitudes for the even numbered subframes and is given the index of 0. The number of magnitudes for subframe number 0 is a variable, designated by L.sub.o.

Input la passes through a logarithmic compander 2a, which performs a log base 2 operation on each of the L.sub.1 magnitudes contained in input la and generates another vector with L.sub.1 elements in the following manner:

y[i]=log.sub.2 (x[i]) for i=1, 2, . . . , L.sub.1, where y[i] represents signal 3a. Compander 2b performs the log base 2 operation on each of the L.sub.0 magnitudes contained in input 1b and generates another vector with L.sub.0 elements in a similar manner: y[i]=log.sub.2 (x[i]) for i=1, 2, . . . L.sub.0, where y[i] represents signal 3b.

Mean calculators 4a and 4b following the companders 2a and 2b calculate means 5a and 5b for each subframe. The mean, or gain value, represents the average speech level for the subframe. Within each frame, two gain values 5a, 5b are determined by computing the mean of the log spectral magnitudes for each of the two subframes and then adding an offset dependent on the number of harmonics within the subframe.

The mean computation of the log spectral magnitudes 3a is calculated as: ##EQU1## where the output, y, represents the mean signal 5a.

The mean computation 4b of the log spectral magnitudes 3b is calculated in a similar manner: ##EQU2## where the output, y, represents the mean signal 5b.

The mean signals 5a and 5b are quantized by a quantizer 6 that is further illustrated in FIG. 8, where the mean signals 5a and 5b are referenced, respectively, as mean1 and mean2. First, an averager 810 averages the mean signals. The output of the averager is 0.5*(mean1+mean2). The average is then quantized by a five-bit uniform scalar quantizer 820. The output of the quantizer 820 forms the first five bits of the output of the quantizer 6. The quantizer output bits are then inverse-quantized by a five-bit uniform inverse scalar quantizer 830. Subtracters 835 then subtract the output of the inverse quantizer 830 from the input values mean1 and mean2 to produce inputs to a five-bit vector quantizer 840. The two inputs constitute a two-dimensional vector (z1 and z2) to be quantized. The vector is compared to each two-dimensional vector consisting of x1(n) and x2(n)) in the table contained in Table A ("Gain VQ Codebook (5-bit)"). The comparison is based on the square distance, e, which is calculated as follows:

e(n)=[x1(n)-z].sup.2 +[x2(n)-z2].sup.2, for n=0, 1, . . . 31. The vector from Table A that minimizes the square distance, e, is selected to produce the last five bits of the output of block 6. The five bits from the output of the vector quantizer 840 are combined with the five bits from the output of the five-bit uniform scalar quantizer 820 by a combiner 850. The output of the combiner 850 is ten bits constituting the output of block 6 which is labeled 21c and is used as an input to the combiner 22 in FIG. 7.

Referring further to the main signal path of the quantizer, the log companded input signals 3a and 3b pass through combiners 7a and 7b that subtract predictor values 33a and 33b from the feedback portion of the quantizer to produce a D.sub.1 (l) signal 8a and a D.sub.1 (0) signal 8b.

Next, the signals 8a and 8b are divided into four frequency blocks using the look-up table in Table O. The table provides the number of magnitudes to be allocated to each of the four frequency blocks based on the total number of magnitudes for the subframe being divided. Since the number of magnitudes contained in any subframe ranges from a minimum of 9 to a maximum of 56, the table contains values for this same range. The length of each frequency block is adjusted such that they are approximately in a ratio of 0.2:0.225:0.275:0.3 to each other and the sum of the lengths equals the number of spectral magnitudes in the current subframe.

Each frequency block is then passed through a discrete cosine transform (DCT) 9a or 9b to efficiently decorrelate the data within each frequency block. The first two DCT coefficients 10a or 10b from each frequency block are then separated out and passed through a 2.times.2 rotation operation 12a or 12b to produce transformed coefficients 13a or 13b. An eight-point DCT 14a or 14b is then performed on the transformed coefficients 13a or 13b to produce a prediction residual block average (PRBA) vector 15a or 15b. The remaining DCT coefficients 11a and 11b from each frequency block form a set of four variable length higher order coefficient (HOC) vectors.

As described above, following the frequency division, each block is processed by the discrete cosine transform blocks 9a or 9b. The DCT blocks use the number of input bins, W, and the values for each of the bins, x(0), x(1), . . . , x(W-1) in the following manner:

The values y(0) and y(1) (identified as 10a) are separated from the other outputs y(2) through y(W-1) (identified as ##EQU3## 11a).

A 2.times.2 rotation operation 12a and 12b is then performed to transform the 2-element input vector 10a and 10b, (x(0),x(1)), into a 2-element output vector 13a and 13b, (y(0),y(1)) by the following rotation procedure:

y(0)=x(0)+sqrt (2)*.times.(1), and y(1)=x(0)-sqrt(2)* x(1).

An 8-point DCT is then performed on the four, 2-element vectors, (x(0),x(1), . . . ,x(7) ) from 13a or 13b according to the following equation: ##EQU4## The output, y(k), is an 8-element PRBA vector 15a or 15b.

Once the prediction and DCT transformation of the individual subframe magnitudes have been completed, both PRBA vectors are quantized. The two eight-element vectors are first combined using a sum-difference transformation 16 into a sum vector and a difference vector. In particular, sum/difference operation 16 is performed on the two 8-element PRBA vectors 15a and 15b, which are represented by x and y respectively, to produce a 16-element vector 17, represented by z, in the following manner:

x(i)=x(i)+y(i), and z(8+i)=x(i)-y(i), for i =0, 1, ... , 7.

These vectors are then quantized using a split vector quantizer 20a where 8, 6, and 7 bits are used for elements 1-2, 3-4, and 5-7 of the sum vector, respectively, and 8 and 6 bits are used for elements 1-3 and 4-7 of the difference vector, respectively. Element 0 of each vector is ignored since it is functionally equivalent to the gain value that is quantized separately.

The quantization of the PRBA sum and difference vectors 17 is performed by the PRBA split-vector quantizer 20a to produce a quantized vector 21a. The two elements z(1) and z(2) constitute a two-dimensional vector to be quantized. The vector is compared to each two-dimensional vector (consisting of x1(n) and x2(n) in the table contained in Table B ("PRBA Sum[1,2] VQ Codebook (8-bit)"). The comparison is based on the square distance, e, which is calculated as follows:

e(n)=[x1 (n)-Z(1)].sup.2 +[x2(n)-z(2)].sup.2, for n=0,1, ..., 255. The vector from Table B that minimizes the square distance, e, is selected to produce the first 8 bits of the output vector 21a.

Next, the two elements z(3) and z(4) constitute a two-dimensional vector to be quantized. The vector is compared to each two-dimensional vector (consisting of x1(n)) and x2(n) in the table contained in Table C ("PRBA Sum[3,4] VQ Codebook (6-bit)"). The comparison is based on the square distance, e, which is calculated as follows:

e(n)=[x1(n)-z(3)].sup.2 +[x2 (n)-z(4)].sup.2, for n=0,1, . . . , 63. The vector from Table C which minimizes the square distance, e, is selected to produce the next 6 bits of the output vector 21a.

Next, the three elements z(5), z(6) and z(7) constitute a three-dimensional vector to be quantized. The vector is compared to each three-dimensional vector (consisting of x1(n), x2(n) and x3(n) in the table contained in Appendix D ("PRBA Sum[5,7] VQ Codebook (7bit)"). The comparison is based on the square distance, e, which is calculated as follows:

e(n)=[x1(n)-z(5)].sup.2 +[x2 (n)-z(6)].sup.2 +[x3 (n)-z (7)].sup.2 for n =0, 1, . . . , 127. The vector from Table D which minimizes the square distance, e, is selected to produce the next 7 bits of the output vector 21a.

Next, the three elements z(9), z(10) and z(11) constitute a three-dimensional vector to be quantized. The vector is compared to each three-dimensional vector (consisting of x1(n), x2(n) and x3(n) in the table contained in Appendix E ("PRBA Dif[1,3] VQ Codebook (8-bit)"). The comparison is based on the square distance, e, which is calculated as follows:

e(n)=[x1(n)-z(9)].sup.2 +[x2(n)-z(10)].sup.2 +[x3(n)-z(11)].sup.2, for n=0,1, . . . , 255. The vector from Table E which minimizes the square distance, e, is selected to produce the next 8 bits of the output vector 21a.

Finally, the four elements z(12), z(13), z(14) and z(15) constitute a four-dimensional vector to be quantized. The vector is compared to each four-dimensional vector (consisting of x1(n), x2(n), x3(n) and x4(n) in the table contained in Table F ("PRBA Dif[4,7] VQ Codebook (6-bit)"). The comparison is based on the square distance, e, which is calculated as: ##EQU5## for n=0,1, . . . , 63. The vector from Table F which minimizes the square distance, e, is selected to produce the last 6 bits of the output vector 21a.

The HOC vectors are quantized similarly to the PRBA vectors. First, for each of the four frequency blocks, the corresponding pair of HOC vectors from the two subframes are combined using a sum-difference transformation 18 that produces a sum and difference vector 19 for each frequency block.

The sum/difference operation is performed separately for each frequency block on the two HOC vectors 11a and 11b, referred to as x and y respectively, to produce a vector, Z.sub.m : ##EQU6## where B.sub.m0 and B.sub.m1 are the lengths of the mth frequency block for, respectively, subframes zero and one, as set forth in Table O, and z is determined for each frequency block (i.e., m equals 0 to 3). The J+K element sum and difference vectors z.sub.m are combined for all four frequency blocks (m equals 0 to 3) to form the HOC sum/difference vector 19.

Due to the variable size of each HOC vector, the sum and difference vectors also have variable, and possibly different, lengths. This is handled in the vector quantization step by ignoring any elements beyond the first four elements of each vector. The remaining elements are vector quantized using seven bits for the sum vector and three bits for the difference vector. After vector quantization is performed, the original sum-difference transformation is reversed on the quantized sum and difference vectors. Since this process is applied to all four frequency blocks a total of forty (4* (7+3)) bits are used to vector quantize the HOC vectors corresponding to both subframes.

The quantization of the HOC sum and difference vectors 19 is performed separately on all four frequency blocks by the HOC split-vector quantizer 20b. First, the vector z.sub.m representing the mth frequency block is separated and compared against each candidate vector in the corresponding sum and difference codebooks contained in the Appendices. A codebook is identified based on the frequency block to which it corresponds and whether it is a sum or difference code. Thus, the "HOC Sum0 VQ Codebook (7-bit)" of Table G represents the sum codebook for frequency block 0. The other codebooks are Table H ("HOC Dif0 VQ Codebook (3-bit)"), Table I ("HOC Sum1 VQ Codebook (7-bit)"), Table J ("HOC Dif1 VQ Codebook (3-bit)"), Table K ("HOC Sum2 VQ Codebook (7-bit)"), Table L ("HOC Dif2 VQ Codebook (3-bit)"), Table M ("HOC Sum2 VQ Codebook (7-bit)"), and Table N ("HOC Dif3 VQ Codebook (3-bit)"). The comparison of the vector z.sub.m for each frequency block with each candidate vector from the corresponding sum codebooks is based upon the square distance, e1.sub.n for each candidate sum vector (consisting of x1(n), x2(n), x3(n) and x4(n)) which is calculated as: ##EQU7## and the square distance e2.sub.m for each candidate difference vector (consisting of x1(n), x2(n), x3(n) and x4(n)), which is calculated as: ##EQU8## where J and K are computed as described above.

The index n of the candidate sum vector from the corresponding sum notebook which minimizes the square distance e1.sub.n is represented with seven bits and the index m of the candidate difference vector which minimizes the square distance e2.sub.m is represented with three bits. These ten bits are combined from all four frequency blocks to form the 40 HOC output bits 21b.

Block 22 multiplexes the quantized PRBA vectors 21a, the quantized mean 21b, and the quantized mean bits 21c to produce output bits 23. These bits 23 are the final output bits of the dual-subframe magnitude quantizer and are also supplied to the feedback portion of the quantizer.

Block 24 of the feedback portion of the dual-subframe quantizer represents the inverse of the functions performed in the superblock labeled Q in the drawing. Block 24 produces estimated values 25a and 25b of D.sub.1 (1) and D.sub.1 (0) (8a and 8b) in response to the quantized bits 23. These estimates would equal D.sub.1 (1) and D.sub.1 (0) in the absence of quantization error in the superblock labeled Q.

Block 26 adds a scaled prediction value 33a, which equals 0.8* P.sub.1 (l), to the estimate of D.sub.1 (l) 25a to produce an estimate M.sub.1 (1) 27. Block 28 time-delays the estimate M.sub.1 (1) 27 by one frame (40 ms) to produce the estimate M.sub.1 (-1) 29.

A predictor block 30 then interpolates the estimated magnitudes and resamples them to produce L.sub.1 estimated magnitudes after which the mean value of the estimated magnitudes is subtracted from each of the L.sub.1 estimated magnitudes to produce the P.sub.1 (1) output 31a. Next, the input estimated magnitudes are interpolated and resampled to produce L.sub.0 estimated magnitudes after which the mean value of the estimated magnitudes is subtracted from each of the L.sub.0 estimated magnitudes to produce the P.sub.1 (0) output 31b.

Block 32a multiplies each magnitude in P.sub.1 (l) 31a by 0.8 to produce the output vector 33a which is used in the feedback element combiner block 7a. Likewise, block 32b multiplies each magnitude in P.sub.1 (1) 31b by 0.8 to produce the output vector 33b which is used in the feedback element combiner block 7b. The output of this process is the quantized magnitude output bits 23, which form the encoder spectral bits for the current frame.

Experimentation has shown that the PRBA and HOC sum vectors are typically more sensitive to bit errors than the corresponding difference vectors. In addition, the PRBA sum vector is typically more sensitive than the HOC sum vector. These relative sensitivities are employed in a prioritization scheme which orders the bits according to their relative sensitivity to bit errors. Generally, the most significant fundamental bits and average gain bits are followed by the PRBA sum bits and the HOC sum bits, and these are followed by the PRBA difference bits and HOC difference bits, followed by any remaining bits. Prioritization is followed by FEC encoding and interleaving to form the encoder output bit stream. FEC encoding may employ block codes or convolution codes. However, in the described embodiment, one [24,12] extended Golay code protects the 12 highest priority (i.e., the most sensitive) bits, three [23,12] Golay codes protect the 36 next highest priority bits and two [14,11] Hamming codes protect the 22 next highest priority bits. The remaining 33 bits per frame are unprotected.

The corresponding decoder is designed to reproduce high quality speech from the encoded bit stream after it is transmitted and received across the channel. The decoder first deinterleaves each frame and performs error correction decoding to correct and/or detect certain likely bit error patterns. To achieve adequate performance over the mobile communications channel, all error correction codes are typically decoded up to their full error correction capability. Next, the FEC decoded bits are used by the decoder to reassemble the quantization bits for the frame from which the model parameters representing the two subframes within the frame are reconstructed.

The AMBE.RTM. decoder uses the reconstructed log spectral magnitudes to synthesize a set of phases which are used by the voiced synthesizer to produce natural sounding speech. The use of synthesized phase information significantly lowers the transmitted data rate, relative to a system which directly transmits this information or its equivalent between the encoder and decoder. The decoder then applies spectral enhancement to the reconstructed spectral magnitudes in order to improve the perceived quality of the speech signal. The decoder further checks for bit errors and smooths the reconstructed parameters if the local estimated channel conditions indicate the presence of possible uncorrectable bit errors. The enhanced and smoothed model parameters (fundamental frequency, V/UV decisions, spectral magnitudes and synthesized phases) are used in speech synthesis. In general, the decoder performs the procedures illustrated in FIGS. 5 and 7, but in reverse.

The reconstructed parameters form the input to the decoder's speech synthesis algorithm which interpolates successive frames of model parameters into smooth segments of speech. The synthesis algorithm uses a set of harmonic oscillators (or an FFT equivalent at high frequencies) to synthesize the voiced speech. This is added to the output of a weighted overlap-add algorithm to synthesize the unvoiced speech. The sums form the synthesized speech signal which is output to a D-to-A converter for playback over a speaker. While this synthesized speech signal may not be close to the original on a sample-by-sample basis, it is perceived as the same by a human listener.

Other embodiments are within the scope of the following claims.

______________________________________Table of Gain VQ Codebook (5 Bit) Valuesn x1(n) x2(n)______________________________________0 -6696 66991 -5724 56412 -4860 48543 -3861 38244 -3132 30915 -2538 26306 -2052 20887 -1890 14918 -1269 16279 -1350 100310 -756 111111 -864 51412 -324 62313 -486 16214 -297 -10915 54 37916 21 -4917 326 12218 21 -44119 522 -19620 348 -68621 826 -46622 630 -100523 1000 -132324 1174 -80925 1631 -127426 1479 -178927 2088 -196028 2566 -252429 3132 -318530 3958 -399431 5546 -5978______________________________________ ______________________________________Table of PRBA Sum[1, 2] VQ Codebook (8 Bit) Valuesn x1(n) x2(n)______________________________________0 -2022 -13331 -1734 -9922 -2757 -6643 -2265 -9534 -1609 -18125 -1379 -12426 -1412 -8157 -1110 -8948 -2219 -4679 -1780 -61210 -1931 -18511 -1570 -27012 -1484 -57913 -1287 -48714 -1327 -19215 -1123 -33616 -857 -79117 -741 -110518 -1097 -61519 -841 -52820 -641 -190221 -554 -82022 -693 -62323 -470 -55724 -939 -36725 -816 -23626 -1051 -14027 -680 -18428 -657 -43329 -449 -41830 -534 -28631 -529 -6732 -2597 033 -2243 034 -3072 1135 -1902 17836 -1451 4637 -1305 25838 -1804 50639 -1561 46040 -3194 63241 -2085 67842 -4144 73643 -2633 92044 -1634 90845 -1146 59246 -1670 146047 -1098 107548 -1056 7049 -864 -4850 -972 29651 -841 15952 -672 -753 -534 11254 -375 24255 -411 20156 -921 64657 -839 44458 -700 144259 -698 72360 -654 46261 -482 36162 -459 80163 -429 57564 -376 -132065 -280 -95066 -372 -69567 -234 -52068 -198 -71569 -63 -94570 -92 -45571 -37 -62572 -403 -19573 -327 -35074 -395 -5575 -280 -18076 -195 -33577 -90 -31078 -146 -20579 -79 -11580 36 -119581 64 -165982 46 -44183 147 -39184 161 -74485 238 -93686 175 -55287 292 -50288 10 -30489 91 -24390 0 -19991 24 -11392 186 -29293 194 -18194 119 -13195 279 -12596 -234 097 -131 098 -347 8699 -233 172100 -113 86101 -6 0102 -107 208103 -6 93104 -308 373105 -168 503106 -378 1056107 -257 769108 -119 345109 -92 790110 -87 1085111 -56 1789112 99 -25113 188 -40114 60 185115 91 75116 188 45117 276 85118 194 175119 289 230120 0 275121 136 335122 10 645123 19 450124 216 475125 261 340126 163 800127 292 1220128 349 -677129 438 -968130 302 -658131 401 -303132 495 -1386133 578 -743134 455 -517135 512 -402136 294 -242137 368 -171138 310 -11139 379 -83140 483 -165141 509 -281142 455 -66143 536 -50144 676 -1071145 770 -843146 842 -434147 646 -575148 823 -630149 934 -989150 774 -438151 951 -418152 592 -186153 600 -312154 646 -79155 695 -170156 734 -288157 958 -268158 936 -87159 837 -217160 364 112161 418 25162 413 206163 465 125164 524 56165 566 162166 498 293167 583 268168 361 481169 399 343170 304 643171 407 912172 513 431173 527 612174 554 1618175 606 750176 621 49177 718 0178 674 135179 688 238180 748 90181 879 36182 790 198183 933 189184 647 378185 795 405186 648 495187 714 1138188 795 594189 832 301190 817 886191 970 711192 1014 -1346193 1226 -870194 1026 -657195 1194 -429196 1462 -1410197 1539 -1146198 1305 -629199 1460 -752200 1010 -94201 1172 -253202 1030 58203 1174 -53204 1392 -106205 1422 -347206 1273 82207 1581 -24208 1793 -787209 2178 -629210 1645 -440211 1872 -468212 2231 -999213 2782 -782214 2607 -296215 3491 -639216 1802 -181217 2108 -283218 1828 171219 2065 60220 2458 4221 3132 -153222 2765 46223 3867 41224 1035 318225 1113 194226 971 471227 1213 353228 1356 228229 1484 339230 1363 450231 1558 540232 1090 908233 1142 589234 1073 1248235 1368 1137236 1372 728237 1574 901238 1479 1956239 1498 1567240 1588 184241 2092 460242 1798 468243 1844 737244 2433 353245 3030 330246 2224 714247 3557 553248 1728 1221249 2053 975250 2038 1544251 2480 2136252 2689 775253 3448 1098254 2526 1106255 3162 1736______________________________________ ______________________________________Table of PRBA Sum[3,4] VQ Codebook (6 Bit) Valuesn x1(n) x2(n) n x1(n) x2(n)______________________________________0 -1320 -848 32 203 -9611 -820 -743 33 184 -3972 -440 -972 34 370 -5503 -424 -584 35 358 -2794 -715 -466 36 135 -1995 -1155 -335 37 135 -56 -627 -243 38 277 -1117 -402 -183 39 444 -928 -165 -459 40 661 -7449 -385 -378 41 593 -35510 -160 -716 42 1193 -63411 77 -594 43 933 -43212 -198 -277 44 797 -19113 -204 -115 45 611 -6514 -6 -362 46 1125 -13015 -22 -173 47 1700 -2416 -841 -86 48 143 18317 -1178 206 49 288 26218 -551 20 50 307 6019 -414 209 51 478 15320 -713 252 52 189 45721 -770 665 53 78 96722 -433 473 54 445 39323 -361 818 55 386 69324 -338 17 56 819 6725 -148 49 57 681 26626 -5 -33 58 1023 27327 -10 124 59 1351 28128 -195 234 60 708 55129 -129 469 61 734 101630 9 316 62 983 61831 -43 647 63 1751 723______________________________________ ______________________________________Table of PRBA Sum[5, 7] VQ Codebook (8 Bit) Valuesn x1(n) x2(n) x3(n)______________________________________0 -473 -644 -1661 -334 -483 -4392 -688 -460 -1473 -387 -391 -1084 -613 -253 -2645 -291 -207 -3226 -592 -230 -307 -334 -92 -1278 -226 -276 -1089 -140 -245 -26410 -248 -805 911 -183 -506 -10812 -205 -92 -59513 -22 -92 -24414 -151 -138 -3015 -43 -253 -14716 -822 -308 -20817 -372 -563 8018 -557 -518 24019 -253 -548 36820 -504 -263 16021 -319 -158 4822 -491 -173 52823 -279 -233 28824 -239 -268 6425 -94 -563 17626 -147 -338 22427 -107 -338 52828 -133 -203 9629 -14 -263 3230 -107 -98 35231 -1 -248 25632 -494 -52 -34533 -239 92 -25734 -485 -72 -3235 -383 153 -8236 -375 194 -40737 -205 543 -38238 -536 379 -5739 -247 338 -20740 -171 -72 -22041 -35 -72 -39542 -188 -11 -3243 -26 -52 -9544 -94 71 -20745 -9 338 -24546 -154 153 -7047 -18 215 -13248 -709 78 7849 -316 78 7850 -462 -57 23451 -226 100 27352 -259 325 11753 -192 618 054 -507 213 31255 -226 348 39056 -68 -57 7857 -34 33 1958 -192 -57 15659 -192 -12 58560 -113 123 11761 -57 280 1962 -12 348 26363 -12 78 23464 60 -383 -30465 84 -473 -58966 12 -495 -15367 204 -765 -24768 108 -135 -20969 156 -360 -7670 60 -180 -3871 192 -158 -3872 204 -248 -45673 420 -495 -24774 408 -293 -5775 744 -473 -1976 480 -225 -47577 768 -68 -28578 276 -225 -22879 480 -113 -19080 0 -403 8881 210 -472 12082 100 -633 40883 180 -265 52084 50 -104 12085 130 -219 10486 110 -81 29687 190 -265 31288 270 -242 8889 330 -771 10490 430 -403 23291 590 -219 50492 350 -104 2493 630 -173 10494 220 -58 13695 370 -104 24896 67 63 -23897 242 -42 -31498 80 105 -8699 107 -42 -29100 175 126 -542101 202 168 -238102 107 336 -29103 242 168 -29104 458 168 -29104 458 168 -371105 458 252 -162106 369 0 -143107 377 63 -29108 242 378 -295109 917 525 -276110 256 588 -67111 310 336 28112 72 42 120113 188 42 46114 202 147 212115 246 21 527116 14 672 286117 43 189 101118 57 147 379119 1595 420 527120 391 105 138121 608 105 46122 391 126 342123 927 63 231124 585 273 175125 579 546 212126 289 378 286127 637 252 619______________________________________ ______________________________________Table of PRBA Dif[1, 3] VQ Codebook (8 Bit) Valuesn x1(n) x2(n) x3(n)______________________________________0 -1153 -430 -5041 -1001 -626 -8612 -1240 -846 -2523 -805 -748 -2524 -1675 -381 -3365 -1175 -111 -5466 -892 -307 -3157 -762 -111 -3368 -566 -405 -7359 -501 -846 -48310 -631 -503 -42011 -370 -479 -25212 -523 -307 -46213 -327 -185 -29414 -631 -332 -23115 -544 -136 -27316 -1170 -348 -2417 -949 -564 -9618 -897 -372 12019 -637 -828 14420 -845 -108 -9621 -676 -132 12022 -910 -324 55223 -624 -108 43224 -572 -492 -16825 -416 -276 -2426 -598 -420 4827 -390 -324 33628 -494 -108 -9629 -429 -276 -16830 -533 -252 14431 -364 -180 16832 -1114 107 -28033 -676 64 -24934 -1333 -86 -12535 -913 193 -23336 -1460 258 -34937 -1114 473 -48138 -949 451 -10939 -639 559 -14040 -384 -43 -35741 -329 43 -18742 -603 43 -4743 -365 86 -144 -566 408 -40445 -329 387 -21846 -603 258 -20247 -511 193 -1648 -1089 94 7749 -732 157 5850 -1482 178 31151 -1014 -53 37052 -751 199 29253 -582 388 13654 -789 220 60455 -751 598 38956 -432 -32 21457 -414 -53 1958 -526 157 23359 -320 136 23360 -376 3040 3861 -357 325 21462 -470 388 35063 -357 199 42864 -285 -592 -58965 -245 -345 -34266 -315 -867 -22867 -205 -400 -11468 -270 -97 -57069 -170 -97 -34270 -280 -235 -15271 -260 -97 -11472 -130 -592 -26673 -40 -290 -64674 -110 -235 -22875 -35 -235 -5776 -35 -97 -24777 -10 -15 -15278 -120 -152 -13379 -85 -42 -7680 -295 -472 8681 -234 -248 082 -234 -216 60383 -172 -520 30184 -286 -40 2185 -177 -88 086 -253 -72 32287 -191 -136 12988 -53 -168 2189 -48 -328 8690 -105 -264 23691 -67 -136 12992 -53 -40 2193 -6 -104 -4394 -105 -40 19395 -29 -40 34496 -176 123 -20897 -143 0 -18298 -309 184 -15699 -205 20 -91100 -276 205 -403101 -229 615 -234102 -238 225 -13103 -162 307 -91104 -81 61 -117105 -10 102 -221106 -105 20 -39107 -48 82 -26108 -124 328 -286109 -24 205 -143110 -143 164 -78111 -20 389 -104112 -270 90 93113 -185 72 0114 -230 0 186115 -131 108 124116 -243 558 0117 -212 432 155118 -171 234 186119 -158 126 279120 -108 0 93121 -36 54 62122 -41 144 480123 0 54 170124 -90 180 62125 4 162 0126 -117 558 256127 -81 342 77128 52 -363 -357129 52 -231 -186130 37 -627 15131 42 -396 -155132 33 -66 -465133 80 -66 -140134 71 -165 -31135 90 -33 -16136 151 -198 -140137 332 -1023 -186138 109 -363 0139 204 -165 -16140 180 -132 -279141 284 -99 -155142 151 -66 -93143 185 -33 15144 46 -170 112145 146 -120 89146 78 -382 292147 78 -145 224148 15 -32 89149 41 -82 22150 10 -70 719151 115 -32 89152 162 -282 134153 304 -345 22154 225 -270 674155 335 -407 359156 256 -57 179157 314 -182 112158 146 -45 404159 241 -195 292160 27 96 -89161 56 128 -362162 4 0 -30163 103 32 -69164 18 432 -459165 61 256 -615166 94 272 -206167 99 144 -550168 113 16 -225169 298 80 -362170 213 48 -50171 255 32 -186172 156 144 -167173 265 320 -24174 122 496 -30175 298 176 -69176 56 66 45177 61 145 112178 32 225 270179 99 13 225180 28 304 45181 118 251 0182 118 808 697183 142 437 157184 156 92 45185 317 13 22186 194 145 270187 260 66 90188 194 834 45189 327 225 45190 189 278 495191 199 225 135192 336 -205 -390193 364 -740 -656194 336 -383 -144195 448 -281 -349196 420 25 -103197 476 -26 -267198 336 -128 -21199 476 -205 -41200 616 -562 -308201 2100 -460 -164202 644 -358 -103203 1148 -434 -62204 672 -230 -595205 1344 -332 -615206 644 -52 -164207 896 -205 -287208 460 -363 176209 560 -660 0210 360 -924 572211 360 -627 198212 420 -99 308213 540 -66 154214 380 99 396215 500 -66 572216 780 -264 66217 1620 -165 198218 640 -165 308219 840 -561 374220 560 66 44221 820 0 110222 760 -66 660223 860 -99 396224 672 246 -360225 840 101 -144226 504 217 -90227 714 246 0228 462 681 -378229 693 536 -234230 399 420 -18231 882 797 18232 1155 188 -216233 1722 217 -396234 987 275 108235 1197 130 126236 1281 594 -180237 1302 1000 -432238 1155 565 108239 1638 304 72240 403 118 183241 557 295 131242 615 265 376243 673 324 673244 384 560 183245 673 501 148246 365 442 411247 384 324 236248 827 147 323249 961 413 411250 1058 177 463251 1443 147 446252 1000 1032 166253 1558 708 253254 692 678 411255 1154 708 481______________________________________ ______________________________________Table of PRBA Dif[1, 3] VQ Codebook (8 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -279 -330 -261 71 -465 -242 -9 72 -248 -66 -189 73 -279 -44 27 2174 -217 -198 -189 -2335 -155 -154 -81 -536 -62 -110 -117 1577 0 -44 -153 -538 -186 -110 63 -2039 -310 0 207 -5310 -155 -242 99 18711 -155 -88 63 712 -124 -330 27 -2313 0 -110 207 -11314 -62 -22 27 15715 -93 0 279 12716 -413 48 -93 -11517 -203 96 -56 -2318 -443 168 -130 13819 -143 288 -130 11520 -113 0 -93 -13821 -53 240 -241 -11522 -83 72 -130 9223 -53 192 -19 -2324 -113 48 129 -9225 -323 240 129 -9226 -83 72 92 4627 -263 120 92 6928 -23 168 314 -6929 -53 360 92 -13830 -23 0 -19 031 7 192 55 20732 7 -275 -296 -4533 63 -209 -72 -1534 91 -253 -8 22535 91 -55 -40 4536 119 -99 -72 -22537 427 -77 -72 -13538 399 -121 -200 10539 175 -33 -104 -7540 7 -99 24 -7541 91 11 88 -1542 119 -165 152 4543 35 -55 88 7544 231 -319 120 -10545 231 -55 184 -16546 259 -143 -8 1547 371 -11 152 4548 60 71 -63 -5549 12 159 -63 -24150 60 71 -21 6951 60 115 -105 16252 108 5 -357 -14853 372 93 -231 -17954 132 5 -231 10055 180 225 -147 756 36 27 63 -14857 60 203 105 -2458 108 93 189 10059 156 335 273 6960 204 93 21 3861 252 159 63 -14862 180 5 21 22463 349 269 63 69______________________________________ ______________________________________Table of HCO Sum0 VQ Codebook (7 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -1087 -987 -785 -1141 -742 -903 -639 -5702 -1363 -567 -639 -3423 -604 -315 -639 -4564 -1501 -1491 -712 10265 -949 -819 -274 06 -880 -399 -493 -1147 -742 -483 -566 3428 -880 -651 237 -1149 -742 -483 -201 -34210 -1294 -231 -128 -11411 -1156 -315 -128 -68412 -1639 -819 18 013 -604 -567 18 34214 -949 -315 310 45615 -811 -315 -55 11416 -384 -666 -282 -59317 -358 -170 -564 -19818 -514 -522 -376 -11919 -254 -378 -188 -27720 -254 -666 -940 -4021 -228 -378 -376 11822 -566 -162 -564 11823 -462 -234 -188 3924 -436 -306 94 -19825 -436 -738 0 -11926 -436 -306 376 -11927 -332 -90 188 3928 -280 -378 -94 59229 -254 -450 5 22930 -618 -162 188 11831 -228 -234 470 35532 -1806 -49 -245 -35833 -860 -49 -245 -19934 -602 341 -49 -35835 -602 146 -931 -25236 -774 81 49 1337 -602 81 49 38438 -946 3341 -440 22539 -688 406 -147 -9340 -860 -49 147 -41141 -688 -49 147 -41142 -1290 276 49 -30543 -774 926 147 -25244 -1462 146 343 6645 -1032 -49 441 -4046 -946 471 147 17247 -516 211 539 17248 -481 -28 -290 -43549 -277 -28 -351 -19550 -345 687 -107 -37551 -294 247 -107 -13552 -362 27 -46 -1553 -328 82 -290 34554 -464 192 -229 4555 -396 467 -351 10556 -396 -83 442 -43557 -243 82 259 -25558 -447 82 15 -25559 -294 742 564 -13560 -260 -83 15 22561 -243 192 259 46562 -328 247 137 -1563 -226 632 137 10564 -170 -641 -436 -22165 130 -885 -187 -27366 -30 -153 -519 -37767 30 -519 -851 -53368 -170 -214 -602 -6569 -70 -641 -270 24770 -150 -214 -104 3971 -10 -31 -270 19572 10 -458 394 -11773 70 -519 -21 -22174 -130 -275 145 -48175 -110 -31 62 -22176 -110 -641 228 9177 70 -275 -21 3978 -90 -214 145 -6579 -30 30 -21 3980 326 -587 -490 -7281 821 -252 -490 -18682 146 -252 -266 -7283 506 -185 -210 -35784 281 -252 -378 27085 551 -319 -154 15686 416 -51 -266 -1587 596 16 -378 38488 506 -319 182 -24389 776 -721 70 9990 236 -185 70 -18691 731 -51 126 9992 191 -386 -98 15693 281 -989 -154 49894 281 -185 14 21395 281 -386 350 15696 -18 144 -254 -19297 97 144 -410 098 -179 464 -410 -25699 28 464 -98 -192100 -156 144 -176 64101 143 80 -98 0102 -133 336 -98 192103 143 656 -488 128104 -133 208 -20 -576105 74 16 448 -192106 -18 208 58 -128107 120 976 58 0108 5 144 370 192109 120 80 136 384110 74 464 682 256111 120 464 136 64112 181 96 -43 -400113 379 182 -215 -272114 313 483 -559 -336115 1105 225 -43 -80116 181 225 -559 240117 643 182 -473 -80118 313 225 -129 112119 511 397 -43 -16120 379 139 215 48121 775 182 559 48122 247 354 301 -272123 643 655 301 -16124 247 53 731 176125 445 10 215 560126 577 526 215 368127 1171 569 387 176______________________________________ ______________________________________Table of HOC Dif0 VQ Codebook (3 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -558 -117 0 01 -248 195 88 -222 -186 -312 -176 -443 0 0 0 774 0 -117 154 -885 62 156 -176 -556 310 -156 -66 227 372 273 110 33______________________________________ ______________________________________Table of HOC Sum1 VQ Codebook (7 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -380 -528 -363 711 -380 -528 -13 142 -1040 -186 -313 -2143 -578 -300 -113 -1574 -974 -471 -163 715 -512 -300 -313 2996 -578 -129 37 1857 -314 -186 -113 718 -446 -357 237 -3859 -380 -870 237 1410 -776 -72 187 -4311 -446 -243 87 -10012 -644 -414 387 7113 -578 -642 87 -10014 -1304 -15 237 12815 -644 -300 187 47016 -221 -452 -385 -30917 -77 -200 -165 -17918 -221 -200 -110 -50419 -149 -200 -440 -11420 -221 -326 0 27621 -95 -662 -165 40622 -95 -32 -220 1623 -23 -158 -440 14624 -167 -410 220 -11425 -95 -158 110 1626 -203 -74 220 -24427 -59 -74 385 -11428 -275 -116 165 21129 -5 -452 220 34130 -113 -74 330 47131 -77 -116 0 21132 -642 57 -143 -40633 -507 0 -371 -7034 -1047 570 -143 -1435 -417 855 -200 4236 -912 0 -143 9837 -417 171 -143 26638 -687 285 28 9839 -372 513 -371 15440 -822 0 427 -29441 -462 171 142 -23842 -1047 342 313 -7043 -507 570 142 -40644 -552 114 313 43445 -462 57 28 -7046 -507 342 484 21047 -507 513 85 4248 -210 40 -140 -22649 -21 0 0 -5450 -336 360 -210 -22651 -126 280 70 -31252 -252 200 0 -1153 -63 160 -420 16154 -168 240 -210 3255 -42 520 -280 -5456 -336 0 350 3257 -126 240 420 -26958 -315 320 280 -5459 -147 600 140 3260 -336 120 70 16161 -63 120 140 7562 -210 360 70 33363 -63 200 630 11864 168 -793 -315 -17165 294 -273 -378 -39966 147 -117 -126 -5767 231 -169 -378 -11468 0 -325 -63 069 84 -481 -252 17170 105 -221 -189 22871 294 -273 0 45672 126 -585 0 -11473 147 -325 252 -22874 147 -169 63 -17175 315 -13 567 -17176 126 -377 504 5777 147 -273 63 5778 63 -169 252 17179 273 -117 63 5780 736 -332 -487 -9681 1748 -179 -192 -3282 736 -26 -369 -41683 828 -26 -192 -3284 460 -638 -251 16085 736 -230 -133 28886 368 -230 -133 3287 552 -77 -487 54488 736 -434 44 -3289 1104 -332 -74 -3290 460 -281 -15 -22491 644 -281 398 -16092 368 -791 221 3293 460 -383 103 3294 644 -281 162 22495 1012 -179 339 16096 76 108 -341 -24497 220 54 -93 -48898 156 378 -589 -12299 188 216 -155 0100 28 0 -31 427101 108 0 31 61102 -4 162 -93 183103 204 432 -217 305104 44 162 31 -122105 156 0 217 -427106 44 810 279 -122107 204 378 217 -305108 124 108 217 244109 220 108 341 -61110 44 432 217 0111 156 432 279 427112 300 -13 -89 -163113 550 237 -266 -13114 450 737 -30 -363115 1050 387 -30 -213116 300 -13 -384 137117 350 87 -89 187118 300 487 -89 -13119 900 237 -443 37120 500 -13 88 -63121 700 187 442 -13122 450 237 29 -263123 700 387 88 37124 300 187 88 37125 350 -13 324 237126 600 237 29 387127 700 687 442 187______________________________________ ______________________________________Table of HOC Dif1 VQ Codebook (3 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -173 -285 5 281 -35 19 -179 762 -357 57 51 -203 -127 285 51 -204 11 -19 5 -1165 333 -171 -41 286 11 -19 143 1247 333 209 -41 -36______________________________________ ______________________________________Table of HOC Sum2 VQ Codebook (7 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -738 -670 -429 -1791 -450 -335 -99 -532 -450 -603 -99 1153 -306 -201 -231 1574 -810 -201 -33 -1375 -378 -134 -231 -3056 -1386 -67 -33 -957 -666 -201 -363 2838 -450 -402 297 -539 -378 -670 561 -1110 -1098 -402 231 32511 -594 -1005 99 -1112 -882 0 99 15713 -810 -268 363 -17914 -594 -335 99 28315 -306 -201 165 15716 -200 -513 -162 -28817 -40 -323 -162 -9618 -200 -589 -378 41619 -56 -513 -378 -3220 -248 -285 -522 3221 -184 -133 -18 -3222 -120 -19 -234 9623 -56 -133 -234 41624 -200 -437 -18 9625 -168 -209 414 -28826 -152 -437 198 54427 -56 -171 54 16028 -184 -95 54 -41629 -152 -171 198 -3230 -280 -171 558 9631 -184 -19 270 28832 -463 57 -228 4033 -263 114 -293 -17634 -413 57 32 47235 -363 228 -423 20236 -813 399 -358 -6837 -563 399 32 -12238 -463 342 -33 20239 -413 627 -163 20240 -813 171 162 -33841 -413 0 97 -17642 -513 57 422 -1443 -463 0 97 9444 -663 570 357 -23045 -313 855 227 -1446 -1013 513 162 4047 -813 228 552 25648 -225 82 0 6349 -63 246 -80 6350 -99 82 -80 27351 -27 246 -320 6352 -81 697 -240 -35753 -45 410 -640 -14754 -261 369 -160 -10555 -63 656 -80 6356 -261 205 240 -2157 -99 82 0 -14758 -171 287 560 10559 9 246 160 18960 -153 287 0 -35761 -99 287 400 -31562 -225 492 240 23163 -45 328 80 -6364 105 -989 -124 -10265 185 -453 -389 -37266 145 -788 41 16867 145 -252 -289 16868 5 -118 -234 -5769 165 -118 -179 -28270 145 -185 -69 -5771 225 -185 -14 30372 105 -185 151 -23773 225 -587 261 -28274 65 -386 151 7875 305 -252 371 -14776 245 -51 96 -5777 265 16 316 -23778 45 185 536 7879 205 -185 261 21380 346 -544 -331 -3081 913 -298 -394 -20782 472 -216 -583 2983 598 -339 -142 20684 472 -175 -268 -20785 598 -52 -205 2986 346 -11 -457 44287 850 -52 -205 38388 346 -380 -16 -3089 724 -626 47 -8990 409 -380 236 20691 1291 -216 -16 2992 472 -11 47 -44393 535 -134 47 -3094 346 -52 -79 14795 787 -175 362 2996 85 220 -195 -17097 145 110 -375 -51098 45 55 -495 -3499 185 55 -195 238100 245 440 -75 -374101 285 825 -75 102102 85 330 -255 374103 185 330 -75 102104 25 110 285 -34105 65 55 -15 34106 65 0 105 102107 225 55 105 510108 105 110 45 -238109 325 550 165 -102110 105 440 405 34111 265 165 165 102112 320 112 -32 -74113 896 194 -410 10114 320 114 -284 10115 512 276 -95 220116 448 317 -410 -326117 1280 399 -32 -74118 384 481 -473 220119 448 399 -158 10120 512 71 157 52121 640 276 -32 -74122 320 153 472 220123 896 30 31 52124 512 276 283 -242125 832 645 31 -74126 448 522 157 304127 960 276 409 94______________________________________ ______________________________________Table of HOC Dif2 VQ Codebook (3 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -224 -237 15 -91 -36 -27 -195 -272 -365 113 36 93 -36 288 -27 -94 58 8 57 1715 199 -237 57 -96 -36 8 120 -817 340 113 -48 -9______________________________________ ______________________________________Table of HOC Sum3 VQ Codebook (7 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -812 -216 -483 -1291 -532 -648 -207 -1292 -868 -504 0 2153 -532 -264 -69 1294 -924 -72 0 -435 -644 -120 -69 -2156 -868 -72 -345 -3017 -476 -24 -483 3448 -756 -216 276 2159 -476 -360 414 010 -1260 -120 0 25811 -476 -264 69 43012 -924 24 552 -4313 -644 72 276 -12914 -476 24 0 4315 -420 24 345 17216 -390 -357 -406 017 -143 -471 -350 -18618 -162 -471 -182 31019 -143 -699 -3550 18620 -390 -72 -350 -31021 -219 42 -126 -18622 -333 -72 -182 6223 -181 -129 -238 49624 -371 -243 154 -12425 -200 -300 -14 -43426 -295 -813 154 12427 -181 -471 42 -6228 -333 -129 434 -31029 -105 -72 210 -6230 -257 -186 154 12431 -143 -243 -70 -6232 -704 195 -366 -12733 -448 91 -183 -3534 -576 91 -122 28735 -448 299 -244 10336 -1216 611 -305 5737 -384 507 -244 -12738 -704 559 -488 14939 -640 455 -183 37940 -1344 351 122 -26541 -640 351 -61 -3542 -960 299 61 14943 -512 351 244 33344 -896 507 -61 -12745 -576 455 244 -31146 -768 611 427 1147 -576 871 0 10348 -298 118 -435 2949 -196 290 -195 -2950 -349 247 -15 8751 -196 247 -255 26152 -400 677 -555 -20353 -349 333 -15 -43554 -264 419 -75 43555 -213 720 -255 8756 -349 204 45 -20357 -264 75 165 2958 -264 75 -15 26159 -145 118 -15 2960 -298 505 45 -14561 -179 290 345 -20362 -315 376 225 2963 -162 462 -15 14564 -76 -129 -424 -5965 57 -43 -193 -24766 -19 -86 -578 27067 133 -258 -270 17668 19 -43 -39 -1269 190 0 -578 -20070 -76 0 -193 12971 171 0 -193 3572 95 -258 269 -1273 152 -602 115 -15374 -76 -301 346 41175 190 -473 38 17676 19 -172 115 -29477 76 -172 577 -15378 -38 -215 38 12979 114 -86 38 31780 208 -338 -132 -14481 649 -1958 -462 -96482 453 -473 -462 10283 845 -68 -198 10284 502 -68 -396 -22685 943 -68 0 -30886 404 -68 -198 10287 600 67 -528 18488 453 -338 132 -30889 796 -608 0 -6290 355 -473 396 18491 551 -338 0 18492 208 -203 66 -6293 698 -203 462 -6294 208 -68 264 26695 551 -68 132 2096 -98 269 -281 -29097 21 171 49 -17498 4 220 -83 5899 106 122 -215 464100 21 465 -149 -116101 21 318 -347 0102 -98 514 -479 406103 123 514 -83 174104 -13 122 181 -406105 140 24 247 -58106 -98 220 511 174107 -30 73 181 174108 4 759 181 -174109 21 318 181 58110 38 318 115 464111 106 710 379 174112 289 270 -162 -135113 289 35 -216 -351114 289 270 -378 189115 561 129 -54 -27116 357 552 -162 -351117 765 364 -324 -27118 221 270 -108 189119 357 740 -432 135120 221 82 0 81121 357 82 162 -243122 561 129 -54 459123 1241 129 108 189124 221 364 162 -189125 425 050 -54 27126 425 270 378 135127 765 364 108 135______________________________________ ______________________________________Table of HOC Dif3 VQ Codebook (3 Bit) Valuesn x1(n) x2(n) x3(n) x4(n)______________________________________0 -94 -248 60 01 0 -17 -100 -902 -376 -17 40 183 -141 247 -80 364 47 -50 -80 1625 329 -182 20 -186 0 49 200 07 282 181 -20 -18______________________________________ ______________________________________Table of Frequency Block Sizes Number of Number of Number ofTotal Number of magnitudes magnitudes magnitudesnumber of magnitudes for for for forsub-frame Frequency Frequency Frequency Frequencymagnitudes Block 1 Block 2 Block 3 Block 4______________________________________9 2 2 2 310 2 2 3 311 2 3 3 312 2 3 3 413 3 3 3 414 3 3 4 415 3 3 4 516 3 4 4 517 3 4 5 518 4 4 5 519 4 4 5 620 4 4 6 621 4 5 6 622 4 5 6 723 5 5 6 724 5 5 7 725 5 6 7 726 5 6 7 827 5 6 8 828 6 6 8 829 6 6 8 930 6 7 8 931 6 7 9 932 6 7 9 1033 7 7 9 1034 7 8 9 1035 7 8 10 1036 7 8 10 1137 8 8 10 1139 8 9 11 1140 8 9 11 1241 8 9 11 1342 8 9 12 1343 8 10 12 1344 9 10 12 1345 9 10 12 1446 9 10 13 1447 9 11 13 1448 10 11 13 1449 10 11 13 1550 10 11 14 1551 10 12 14 1552 10 12 14 1653 11 12 14 1654 11 12 15 1655 11 12 15 1756 11 13 15 17______________________________________

Claims

1. A method of encoding speech into a frame of bits, the method including:

digitizing a speech signal into a sequence of digital speech samples;

dividing the digital speech samples into a sequence of subframes, each of the subframes including multiple digital speech samples;

estimating a set of speech model parameters for each subframe, wherein the speech model parameters include a set of spectral magnitude parameters that represent spectral magnitude information for the subframe;

combining consecutive subframes from the sequence of subframes into a frame;

jointly quantizing the spectral magnitude parameters from the consecutive subframes of the frame to produce a set of encoder spectral bits, wherein:

the joint quantization includes forming predicted spectral magnitude parameters from quantized spectral magnitude parameters from a previous subframe;

a subframe of the frame includes a number of spectral magnitude parameters that may vary from a number of spectral magnitude parameters in the previous subframe; and

the joint quantization accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe; and

including the encoder spectral bits in a frame of bits.

2. The method of claim 1, wherein the joint quantization comprises:

computing residual parameters as the difference between the spectral magnitude parameters and the predicted spectral magnitude parameters;

combining the residual parameters from the consecutive subframes within the frame; and

quantizing the combined residual parameters into a set of encoder spectral bits.

3. The method of claim 1, wherein the spectral magnitude parameters correspond to a frequency-domain representation of a spectral envelope of the subframe.

4. The method of claim 1, wherein the number of spectral magnitude parameters in the subframe of the frame may vary from a number of spectral magnitude parameters in a second subframe of the frame; and

the joint quantization accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the second subframe of the frame.

5. The method of claim 4, wherein the joint quantization accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint quantization.

6. The method of claim 1, wherein the joint quantization accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe by interpolating and resampling spectral magnitude parameters for the previous subframe and using the interpolated and resampled spectral magnitude parameters in forming the predicted spectral magnitude parameters.

7. The method of claim 1, wherein the joint quantization accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint quantization.

8. A method of encoding speech into a frame of bits, the method including:

digitizing a speech signal into a sequence of digital speech samples;

dividing the digital speech samples into a sequence of subframes, each of the subframes including multiple digital speech samples;

estimating a set of speech model parameters for each subframe, wherein the speech model parameters include a set of spectral magnitude parameters that represent spectral information for the subframe;

combining consecutive subframes from the sequence of subframes into a frame;

jointly quantizing the spectral magnitude parameters from the consecutive subframes of the frame to produce a set of encoder spectral bits, wherein the joint quantization includes forming predicted spectral magnitude parameters from quantized spectral magnitude parameters from a previous frame; and

including the encoder spectral bits in a frame of bits;

wherein the joint quantization comprises:

computing residual parameters as the difference between the spectral magnitude parameters and the predicted spectral magnitude parameters;

combining the residual parameters from the consecutive subframes within the frame; and

quantizing the combined residual parameters into a set of encoder spectral bits; and

combining the residual parameters from the consecutive subframes within the frame comprises:

dividing the residual parameters from each of the subframes into frequency blocks;

performing a linear transformation on the residual parameters within each frequency block to produce a set of transformed residual coefficients for each subframe;

grouping a minority of the transformed residual coefficients from the frequency blocks for each subframe into a prediction residual block average (PRBA) vector for the subframe;

grouping the remaining transformed residual coefficients for each frequency block of each subframe into a higher order coefficient (HOC) vector for the frequency block;

transforming the PRBA vectors to produce a transformed PRBA vector for each subframe;

combining the transformed PRBA vectors for the subframes of the frame by computing generalized sum and difference vectors from the transformed PRBA vectors; and

combining the HOC vectors within each frequency block for the subframes of the frame by computing generalized sum and difference vectors from the HOC vectors for each frequency block.

9. The method of claim 1, 2 or 8, further comprising producing additional encoder bits by quantizing additional speech model parameters other than the spectral magnitude parameters.

10. The method of claim 9, wherein the additional speech model parameters include parameters representative of a fundamental frequency and parameters representative of a voicing state.

11. The method of claim 1, 2 or 8, wherein the frame of bits includes redundant error control bits protecting at least some of the encoder spectral bits.

12. The method of claim 1, 2 or 8, wherein the spectral magnitude parameters represent log spectral magnitudes estimated for a Multi-Band Excitation (MBE) speech model.

13. The method of claim 12, wherein the spectral magnitude parameters are estimated from a computed spectrum in a manner which is independent of a voicing state.

14. The method of claim 2 or 8, wherein the predicted spectral magnitude parameters are formed by applying a gain of less than unity to a linear interpolation of quantized spectral magnitudes from a last subframe in a previous frame.

15. The method of claim 8, wherein the transformed residual coefficients are computed for each of the frequency blocks using a Discrete Cosine Transform (DCT) followed by a linear two by two transform on two lowest order DCT coefficients.

16. The method of claim 15, wherein the length of each frequency block is approximately proportional to a number of spectral magnitude parameters within the subframe.

17. The method of claim 2 or 8, wherein quantizing the combined residual parameters includes using at least one vector quantizer.

18. The method of claim 8, wherein quantizing the combined residual parameters includes applying vector quantization to all or part of the generalized sum and difference vectors computed from the transformed PRBA vectors and applying vector quantization to all or part of the generalized sum and difference vectors computed from the HOC vectors.

19. The method of claim 18, wherein the frame includes two consecutive subframes from the sequence of subframes.

20. A speech encoder for encoding speech into a frame of bits, the encoder including:

means for digitizing a speech signal into a sequence of digital speech samples;

means for dividing the digital speech samples into a sequence of subframes, each of the subframes including multiple digital speech samples;

means for estimating a set of speech model parameters for each subframe, wherein the speech model parameters include a set of spectral magnitude parameters that represent spectral magnitude information for the subframe;

means for combining consecutive subframes from the sequence of subframes into a frame;

means for jointly quantizing the spectral magnitude parameters from the consecutive subframes of the frame to produce a set of encoder spectral bits, wherein:

the means for jointly quantizing forms predicted spectral magnitude parameters from quantized spectral magnitude parameters from a previous subframe;

a subframe of the frame includes a number of spectral magnitude parameters that may vary from a number of spectral magnitude parameters in the previous subframe; and

the means for jointly quantizing accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe; and

means for forming a frame of bits including the encoder spectral bits.

21. The speech encoder of claim 20, wherein the spectral magnitude parameters correspond to a frequency-domain representation of a spectral envelope of the subframe.

22. The speech encoder of claim 20, wherein the number of spectral magnitude parameters in the subframe of the frame may vary from a number of spectral magnitude parameters in a second subframe of the frame; and

the means for jointly quantizing accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the second subframe of the frame.

23. The speech encoder of claim 22, wherein the means for jointly quantizing accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint quantization.

24. The speech encoder of claim 20, wherein the means for jointly quantizing accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe by interpolating and resampling spectral magnitude parameters for the previous subframe and using the interpolated and resampled spectral magnitude parameters in forming the predicted spectral magnitude parameters.

25. The speech encoder of claim 20, wherein the means for jointly quantizing accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint quantization.

26. A method of decoding speech from a frame of bits, the method comprising:

extracting decoder spectral bits from the frame of bits;

using the decoder spectral bits to jointly reconstruct spectral magnitude parameters for consecutive subframes within a frame of speech, wherein the joint reconstruction includes:

inverse quantizing the decoder spectral bits to reconstruct a set of combined residual parameters for the frame from which separate residual parameters for each of the subframes are computed;

forming predicted spectral magnitude parameters from reconstructed spectral magnitude parameters from a previous subframe; and

adding the separate residual parameters to the predicted spectral magnitude parameters to form the reconstructed spectral magnitude parameters for each subframe within the frame; wherein

a subframe of the frame includes a number of spectral magnitude parameters that may vary from a number of spectral magnitude parameters in the previous subframe; and

the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe; and

synthesizing digital speech samples for each subframe within the frame of speech using speech model parameters which include some or all of the reconstructed voiced/unvoiced metrics and some or all of the reconstructed spectral magnitude parameters for the subframe.

27. The method of claim 26, wherein the spectral magnitude parameters correspond to a frequency-domain representation of a spectral envelope of the subframe.

28. The method of claim 26, wherein the number of spectral magnitude parameters in the subframe of the frame may vary from a number of spectral magnitude parameters in a second subframe of the frame; and

the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the second subframe of the frame.

29. The method of claim 28, wherein the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint reconstruction.

30. The method of claim 26, wherein the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe by interpolating and resampling spectral magnitude parameters for the previous subframe and using the interpolated and resampled spectral magnitude parameters in forming the predicted spectral magnitude parameters.

31. The method of claim 26, wherein the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint reconstruction.

32. A method of decoding speech from a frame of bits, the method comprising:

extracting decoder spectral bits from the frame of bits;

using the decoder spectral bits to jointly reconstruct spectral magnitude parameters for consecutive subframes within a frame of speech, wherein the joint reconstruction includes;

inverse quantizing the decoder spectral bits to reconstruct a set of combined residual parameters for the frame from which separate residual parameters for each of the subframes are computed;

forming predicted spectral magnitude parameters from reconstructed spectral magnitude parameters from a previous frame; and

adding the separate residual parameters to the predicted spectral magnitude parameters to form the reconstructed spectral magnitude parameters for each subframe within the frame; and

synthesizing digital speech samples for each subframe within the frame of speech using speech model parameters which include some or all of the reconstructed spectral magnitude parameters for the subframe;

wherein the computing of the separate residual parameters for each subframe from the combined residual parameters for the frame comprises:

dividing each subframe into frequency blocks;

separating the combined residual parameters for the frame into generalized sum and difference vectors representing transformed PRBA vectors combined across the subframes of the frame, and into generalized sum and difference vectors representing HOC vectors for the frequency blocks combined across the subframes of the frame;

computing PRBA vectors for each subframe from the generalized sum and difference vectors representing the transformed PRBA vectors;

computing HOC vectors for each subframe from the generalized sum and difference vectors representing the HOC vectors for each of the frequency blocks;

combining the PRBA vector and the HOC vectors for each of the frequency blocks to form transformed residual coefficients for each of the subframes; and

performing an inverse transformation on the transformed residual coefficients to produce the separate residual parameters for each subframe of the frame.

33. The method of claim 26, or 32, wherein the frame of bits includes other decoder bits in addition to the decoder spectral bits, wherein the other decoder bits are representative of speech model parameters other than the spectral magnitude parameters.

34. The method of claim 33, wherein the speech model parameters include parameters representative of a fundamental frequency and parameters representative of a voicing state.

35. The method of claim 26 or 32, wherein the reconstructed spectral magnitude parameters represent log spectral magnitudes used in a Multi-Band Excitation (MBE) speech model.

36. The method of claim 26 or 32, wherein the frame of bits includes redundant error control bits protecting at least some of the decoder spectral bits.

37. The method of claim 26 or 32, wherein the synthesizing of speech for each subframe includes computing a set of phase parameters from the reconstructed spectral magnitude parameters.

38. The method of claim 26 or 32, wherein the predicted spectral magnitude parameters are formed by applying a gain of less than unity to a linear interpolation of quantized spectral magnitudes from a last subframe of a previous frame.

39. The method of claim 32, wherein the separate residual parameters are computed from the transformed residual coefficients by performing on each of the frequency blocks an inverse linear two by two transform on the two lowest order transformed residual coefficients within the frequency block and then performing an Inverse Discrete Cosine Transform (IDCT) over all the transformed residual coefficients within the frequency block.

40. The method of claim 39, wherein four of the frequency blocks are used per subframe and wherein the length of each frequency block is approximately proportional to a number of spectral magnitude parameters within the subframe.

41. The method of claims 26 or 32, wherein the inverse quantization to reconstruct a set of combined residual parameters for the frame includes using inverse vector quantization applied to one or more vectors.

42. A decoder for decoding speech from a frame of bits, the decoder including:

means for extracting decoder spectral bits from the frame of bits;

means for using the decoder spectral bits to jointly reconstruct spectral magnitude parameters for consecutive subframes within a frame of speech, wherein the joint reconstruction includes:

inverse quantizing the decoder spectral bits to reconstruct a set of combined residual parameters for the frame from which separate residual parameters for each of the subframes are computed;

forming predicted spectral magnitude parameters from reconstructed spectral magnitude parameters from a previous subframe; and

adding the separate residual parameters to the predicted spectral magnitude parameters to form the reconstructed spectral magnitude parameters for each subframe within the frame; wherein

a subframe of the frame includes a number of spectral magnitude parameters that may vary from a number of spectral magnitude parameters in the previous subframe; and

the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe; and

means for synthesizing digital speech samples for each subframe within the frame of speech using speech model parameters which include some or all of the reconstructed spectral magnitude parameters for the subframe.

43. The method of claim 42, wherein the speech level parameter for each subframe is estimated as a mean of a set of spectral magnitude parameters computed for each subframe plus an offset.

44. The method of claim 43, wherein the spectral magnitude parameters represent log spectral magnitudes estimated for a Multi-Band Excitation (MBE) speech model.

45. The method of claim 43, wherein the offset is dependent on a number of spectral magnitude parameters in the frame.

46. The decoder of claim 42, wherein the spectral magnitude parameters correspond to a frequency-domain representation of a spectral envelope of the subframe.

47. The decoder of claim 42, wherein the number of spectral magnitude parameters in the subframe of the frame may vary from a number of spectral magnitude parameters in a second subframe of the frame; and

the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the second subframe of the frame.

48. The decoder of claim 47, wherein the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint reconstruction.

49. The decoder of claim 42, wherein the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in the subframe of the frame and the number of spectral magnitude parameters in the previous subframe by interpolating and resampling spectral magnitude parameters for the previous subframe and using the interpolated and resampled spectral magnitude parameters in forming the predicted spectral magnitude parameters.

50. The decoder of claim 42, wherein the joint reconstruction accounts for any variation between the number of spectral magnitude parameters in a subframe of the frame and the number of spectral magnitude parameters in a second subframe of the frame by transforming the spectral magnitude parameters for the two subframes to produce one or more output vectors and limiting the number of elements within each output vector that are used in the joint reconstruction.

51. A method of encoding a level of speech into a frame of bits, the method comprising:

digitizing a speech signal into a sequence of digital speech samples;

dividing the digital speech samples into a sequence of subframes, each of the subframes including multiple digital speech samples;

estimating a speech level parameter for each of the subframes, wherein the speech level parameter is representative of the amplitude of the digital speech samples comprising the subframe;

combining a plurality of consecutive subframes from the sequence of subframes into a frame;

jointly quantizing the speech level parameters from the plurality of consecutive subframes within the frame, characterized in that the joint quantization includes computing and quantizing an average level parameter by combining the speech level parameters over the subframes within the frame, and computing and quantizing a difference level vector between the speech level parameters for each subframe within the frame and the average level parameter; and

including quantized bits representative of the average level parameter and the difference level vector in a frame of bits.

52. The method of claim 51 or 43, wherein the difference level vector is quantized using vector quantization.

53. The method of claim 51 or 43, wherein the frame of bits includes error control bits used to protect some or all of the quantized bits representative of the average level parameter and the difference level vector.

54. The method of claim 51, wherein the spectral magnitude parameters correspond to a frequency-domain representation of a spectral envelope of the subframe.