Patent Application
20240334133
This disclosure relates to detection of whether an audio signal in an acoustic system is tonal. More particularly this disclosure relates to detection of whether an audio signal in a hearing device is tonal.
A hearing device typically includes a microphone, a speaker and an amplifier configured to amplify sound received in the form of a signal from the microphone to an amplified signal that is output from the speaker as a sound that is amplified relative to the amplitude of the sound inputted to the microphone. One or more processors may be provided not only to control the amplifier, but to further process the signal. One such further process involves cancellation of feedback that may exist in the signal. Examples of hearing devices include, but are not limited to: headsets, hearing aids, public address systems, telephones, radios, cochlear implants, bone conduction devices and personal listening devices.
A related task that may be carried out by a processor is performed to identify whether the input signal is tonal or not. This determination is especially useful for improving the performance of a feedback cancellation algorithm within a hearing device.
Hearing aid devices are designed to provide gain to amplify sounds to compensate for a user's hearing loss. However, because there is an acoustic path from the speaker of the hearing aid back to the microphone, there is a high risk of instability. This instability may present as a disturbing howling or squealing sound, sometimes referred to as feedback. This instability needs to be removed or controlled if the device is to be comfortably used by a user for an acceptable user experience. This howling is very tonal.
Typically, a system approach is used to control this howling. An example system in a hearing aid has two parts. One part is an adaptive feedback canceller, which continuously models the acoustic path and attempts to cancel the feedback signal coupling from the hearing aid output back into the microphone. Another part is a suppression system that reduces the forward gain when feedback audio artifacts arise, to control transient howling due to movement or handling, and to compensate for slow adaption of the feedback canceller.
An important aspect of a system is to be able to detect the tonal nature of a howl or feedback. Although a tone detector, by itself, does not distinguish between tonal sounds in the environment (such music, beeps, alarms, etc.) and howls caused by feedback, the detection of tones is important for early identification and suppression of feedback, as once a tone is detected, it can be further evaluated, such as by the feedback cancellation system, to determine whether the tone is feedback or a sound in the environment.
Many different approaches have been taken in attempting to reduce the susceptibility of hearing devices, such as hearing aids to feedback. For example, attenuation and notch filtering have been employed in U.S. Pat. No. 4,088,835; and detection of an exponential rise in a periodic signal for early identification of feedback in U.S. Pat. No. 8,942,398.
U.S. Pat. No. 10,097,930 discloses methods for tonality-driven feedback canceler adaptation in which the method includes strength of tonality that is determined by estimating a second derivative of a subband phase of an input signal.
U.S. Pat. No. 7,302,070 discloses a method for identifying oscillation in a signal due to feedback, in which a change in signal phase is calculated for each of a plurality of frequency bands generated by an FFT device from a series of successive time windows of an audio signal to produce a measure of whether oscillation due to feedback is present in the signal. Systems such as these typically require calculations such as arctangent, which are difficult to perform on an embedded fixed-point digital signal processing (DSP) platform.
There is a need in the art for improved methods and systems for detecting tones of an audio signal of a hearing device to allow rapid and efficient detection of tones so that they can be further evaluated and processed to determine whether they are from the sound environment or from feedback. When they are from feedback they can be processed and reduced or eliminated by a feedback cancellation system.
There is a need in the art for more efficient methods and systems for detecting tones of an audio signal of a hearing device, which can be more readily carried out on relatively limited processors that may be provided with some types of hearing devices.
There is a need in the art for more efficient methods and systems for detecting tones of an audio signal of a hearing device, which can reduce the cost (and potentially the size) of tone detection and feedback cancellation systems of hearing devices.
According to an embodiment of the present invention, a method of signal processing an audio signal in a hearing device to determine whether the signal is tonal includes: converting the signal at each of a series of successive time windows into samples in the frequency domain across multiple subbands; calculating for at least one of the subbands a normalized cross-correlation between two different samples in the same subband; and comparing a metric resulting from the calculating to a predetermined threshold to provide a measure of whether the signal is tonal; wherein the signal is considered to be tonal in the frequency of the subband when the metric is greater than or equal to the predetermined threshold and the signal is considered to be not tonal in the frequency of the subband when the metric is less than the predetermined threshold.
In at least one embodiment, the calculating and comparing are performed for each of a plurality of the multiple subbands.
In at least one embodiment, the calculating and comparing are performed for all of the multiple subbands.
In at least one embodiment, the calculating step is iterated for successive samples, and the comparing step is performed relative to an average of the results from the iterated calculation steps.
In at least one embodiment, there is no time overlap corresponding to the two different samples in the frequency or joint time-frequency domain.
In at least one embodiment, the method further includes improving processing efficiency of the calculating step by using at least one of count sign bits (CSB), count leading bits (CLB) or log 2 approximation of absolute value.
In at least one embodiment, when a signal is considered to be tonal, the method further includes: reducing a gain of the signal in the subband where the tonal signal is considered to be.
In at least one embodiment, when a signal is considered to be tonal, the method further includes: providing the tonal signal to a feedback cancellation system configured to determine whether the tonal signal is feedback.
In at least one embodiment, the hearing device is a hearing aid.
In at least one embodiment, the hearing aid is a completely-in-the-canal (CIC) hearing aid.
According to an aspect of the present invention, a hearing device is provided that includes: a microphone; a receiver; and a processor connected to the microphone and the receiver, the processor configured to receive an audio signal from the microphone and process the audio signal and the receiver configured to provide an output signal to a user, the processor further configured to: convert the signal at each of a series of successive time windows into samples in the frequency domain across multiple subbands; calculate for at least one of the subbands a normalized cross-correlation between two different samples in the same subband; and compare a metric resulting from the calculation of the normalized cross-correlation to a predetermined threshold to provide a measure of whether the signal is tonal; wherein the signal is considered to be tonal in the frequency of the subband when the metric is greater than or equal to the predetermined threshold and the signal is considered to be not tonal in the frequency of the subband when the metric is less than the predetermined threshold.
In at least one embodiment, the hearing device is a hearing aid.
In at least one embodiment, the hearing aid is a completely-in-the-canal (CIC) hearing aid.
In at least one embodiment, when a signal is considered to be tonal, the signal is provided for further processing to determine whether the tonal signal is feedback; and when the tonal signal is determined to be feedback, reduce a gain of the signal in the subband where the tonal signal is considered to be.
In at least one embodiment, when a signal is considered to be tonal, the signal is provided for further processing to determine whether the tonal signal is feedback, so that when the tonal signal is determined to be feedback, the feedback can be addressed by a feedback cancellation system to cancel the feedback.
In at least one embodiment, the processor is configured to perform the calculate and compare steps for each of a plurality of the multiple subbands.
In at least one embodiment, the processor is configured to perform the calculate and compare steps for all of the multiple subbands.
In at least one embodiment, the calculate step is iterated for successive samples, and the compare step is performed relative to an average of the results from the iterated calculation steps.
In at least one embodiment, the processor is configured to improve processing efficiency of the calculate step by using at least one of count sign bits (CSB), count leading bits (CLB) or log2 approximation of absolute value.
According to an aspect of the present invention, a hearing device includes: a microphone; a receiver; and a processor connected to the microphone and the receiver, the processor configured to receive an audio signal from the microphone and process the audio signal and the receiver configured to provide an output signal to a user, the processor further configured to: convert the signal at each of a series of successive time windows into samples in the frequency domain across multiple subbands; compare a pair of samples in the frequency domain in a same one of the subbands to calculate a normalized cross-correlation; calculate a metric based on the normalize cross correlation and compare the metric to a predetermined threshold to provide a measure of whether the signal is tonal; wherein the signal is considered to be tonal in the frequency of the subband when the metric is greater than or equal to the predetermined threshold and the signal is considered to be not tonal in the frequency of the subband when the metric is less than the predetermined threshold.
These and other advantages and features of the invention will become apparent to those persons skilled in the art upon reading the details of the methods and devices as more fully described below.
Various embodiments of the present invention are illustrated by way of example in the figures of the accompanying drawings. Such embodiments are demonstrative of the present invention and are not intended to be limiting as to the only embodiments possible, as the invention is defined by the appended claims, as supported by the specification and drawings.
Before the present invention is described, it is to be understood that this invention is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.
Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited.
It must be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a signal” includes a plurality of such signals and reference to “the subband” includes reference to one or more subbands and equivalents thereof known to those skilled in the art, and so forth.
The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.
An “audio processing system” as used herein is a system that includes a microphone and a receiver or speaker, an adaptive feedback canceler for removing feedback, as well as processing electronics for amplification of signals. Examples of audio processing systems include, but are not limited to: listening devices, hearing aids, telephony, public address systems, headsets, audio conference systems, etc.
The terms “tonality” “tonal signal”, “tonal input” “tone” and “tonal”, as used herein refer to audio signals that are larger in signals that are dominated by single-frequency components having slowly varying (or non-varying) frequencies (tones), and smaller in signals that are not comprised of such components.
The terms “bins”, “channels”, “frequency bins” and “binned signals”, as used herein, refer to subbands of a signal resulting from splitting the signal from the time domain to frequency domain, or to the joint time-frequency domain. A bin is an interval in the frequency domain, delimited by a lower frequency and an upper frequency wherein each bin (i.e., subband) is characterized by a different frequency range than the other resulting bins. The terms “bin” or “bins” are used interchangeably with the terms “channel” and “subband”; equivalently the plural terms “bins” or “channels” and “subbands” are also interchangeable herein.
The multiple outputs of each WOLA computation are referred to as subbands or bins, each representing the estimated frequency content of the latest set of time domain samples. There are M subbands (or M bins), each full bin of which contains 1 new complex frequency domain sample (from which magnitude and phase can be computed) for every WOLA computation. Note that the first and last bins may have only half the bandwidth of the other bins and contain only real (not complex frequency domain) data. These half bandwidth bins are therefore not further processed for tone detection, as they don't contain information pertaining to phase that can be analyzed.
“Joint Time-Frequency Analysis”, as used herein, refers to calculations on time-domain data which produce frequency segmentation of the data, but which also advance in time for each calculation.
A “WOLA frame” or “WOLA block” refers to N time-domain samples which are processed together with older time-domain samples using WOLA computations to form 1 frequency-domain (actually joint time-frequency) sample across M frequency bins, wherein N and M are positive integers greater than 1.
A “WOLA analysis frame”, as used herein, refers to P WOLA blocks that are concatenated to form the WOLA analysis frame, where P is a positive integer greater than 1. This WOLA analysis frame includes a WOLA frame or WOLA block of the latest N time-domain samples, along with ((P−1)*N) previous time domain samples, for the total of (P−1)*N+N=P*N time domain samples.
A “WOLA sample”, as used herein, refers to one of the M bins of a WOLA computation (that has been performed on a WOLA analysis frame).
The term “entrainment” as used herein refers to an occurrence when a feedback canceller mistakenly attempts to cancel a tonal input to an audio processing system. This results in the addition of a tone to the original input signal to the audio processing system, especially when the tonal input then goes away.
The term “feedback”, as used herein, refers to the reflection of the output signal back into the input, in a recursive manner, such that the audio processing system goes unstable at some frequency. It is also referred to as ‘positive loop gain’ which includes an acoustic path from the output signal back to the input signal, and the signal processing within the audio processing system.
Hearing devices may be provided with a feedback cancellation system such as an adaptive feedback canceller which continuously monitors the audio signal from the devices' input, and adapts to the feedback signal in that input to provide anti-phase cancellation. When properly functioning, these devices tend to settle to a quiescent state where the feedback path is cancelled. However, one of the causes of feedback that can result in howling is input characterized as tonal. By providing a system that can readily identify tonal signals, this can improve the efficiency and rapidity with which a system can adapt to and suppress feedback. The present invention provides tone detection capability for hearing devices that can detect the presence of tones, which can then be further evaluated as to whether they are resultant from environmental sounds, or from feedback. When they are determined to be feedback, further processing can be carried out to suppress or cancel the feedback.
Entrainment artifacts in audio systems include squealing or howling sounds that can be very annoying to the listener. As noted, such entrainment artifacts may occur with input sounds such as music, tonal parts of speech, beeps, alarms, rings, clicks, pops, etc. Such entrainment artifacts can occur when the input and output signal are strongly self-correlated, which can occur with the examples provided above, as well as others. Self-correlated signals are self-similar over a short time span, that is, similar to slightly delayed versions of themselves. If the signal is similar to a delayed version of itself, then at the hearing aid input, the feedback canceler cannot distinguish new signal from feedback. The simplest case of this self-similarity is a tonal or pitched signal. A periodic signal is identical to versions of itself delayed by the pitch period, and thus tonal signals, like music, are troublesome for adaptive feedback cancelers.
Suppression systems require several parts to detect feedback howling. However, an important aspect is to be able to detect the tonal nature of a howl. The present invention provides a tone detector and an implementation of the tone detector that can be used in a howl suppression system. The tone detector, by itself, does not distinguish between tonal sounds in the environment (such as music) and howls caused by feedback. Other parts of the system are used to differentiate between these stimuli.
This disclosure describes an invention to do the tone detection portion, in a subband processing hearing device, such as a hearing aid system or other hearing device.
The present invention discloses, among other things, apparatus and methods for signal processing an input signal in a hearing device to detect when a signal is tonal or includes tones so that a feedback canceler can be notified when a tone is detected, to further process the signal to determine whether the tone is feedback or results from an environmental sound. If feedback is determined, the feedback can then be mitigated by the feedback cancelation subsystem. If the tone is determined to not be feedback, but rather the result of an environmental sound, the feedback cancelation system will not address the tone.
The present invention increases overall sound quality and/or improves feedback cancellation performance by proactively detecting when the input signal is tonal, and addressing the tone when it is feedback so as to remove or mitigate it, while ignoring the tone when it is determined that the tone is not feedback. Thus the present invention facilitates early mitigation of entrainment in adaptive feedback cancellation while minimizing degradation of the hearing device output, thereby improving sound quality for tonal inputs such as speech and music and other inputs susceptible to entrainment, as described above.
The subband signals 108 are processed for tone detection separately (although typically in a parallel), as described in the following. Cross-correlation calculations per subband are performed by processor 142 of subsystem 140. Processing includes calculation of a normalized cross-correlation between samples of the same frequency bin at different times. Multiple such calculations can be made by iterating this step for successive samples and an average cross-correlation value over multiple samples can be computed from the multiple cross-correlation values. The average cross-correlation value can be approximated by introducing a smoothing factor to the normalized cross-correlation value. A metric used to detect whether a signal is tonal is then calculated as the magnitude (absolute value) of the smoothed, normalized cross-correlation. The metric can then be compared to a threshold value to decide whether a tone is present.
Note that the bins (input in the subband domain) 108 generated at 106 result from processing signal 104 which includes both environmental sounds picked up by the microphone 102 as well as feedback sound that is fed back to the microphone 102 from the receiver/speaker 126 along feedback path 180.
If the metrics calculated by the processor, when compared to the threshold value, indicate that no tone is present, then the subsystem 140 will not make any changes to the adaptive feedback canceler that would be applied to mitigate a tone. The subsystem 140 may perform other functions, such as gain application, noise reduction, etc. 110, to be applied to signal 108 at 112. If on the other hand, a tone is detected, then the feedback canceler of the subsystem 140 will further process the bin or bins in which the tone was detected. A feedback cancellation subsystem such as that described in copending U.S. application Ser. No. 17/239,427 filed Apr. 23, 2021 and titled Detection of Feedback path Change (which is incorporated herein, in its entirety, by reference thereto), or other known feedback cancellation subsystem may be used for further processing to determine whether the detected tone is from an environmental sound, or from feedback. If the tone is determined to be from an environmental sound, again the feedback cancellation subsystem does not make any changes to its feedback suppression settings. If the tone is determined to be feedback, the subsystem 140 may decrease the gain in the frequency(ies) of the bin(s) where tone was detected. Additionally, or alternatively, an adaptation rate of the feedback canceler may be increased so as to more rapidly mitigate the feedback due to the tone. The adaptation rate change could be applied to a subset (less than all of the bins) where feedback is determined to occur, or, alternatively, could be applied to all the bins.
The processed signal subbands 114 resulting from combination of the gain signal 110 from subsystem 140 with the subbands 108 at 112 are further processed using an inverse FFT (IFFT) to perform WOLA synthesis at 116, which returns the signal to the time domain for output through receiver/speaker 126. As noted, while in the joint time-frequency domain, there is processing to allow gain to be applied in the frequency domain, as well as feedback cancellation and noise reduction, among others.
The audio input at 106 in
The complex results within each frequency subband represent the magnitude and phase in the frequency subband at a given point in time. These complex-valued results created for each WOLA block of data can be analyzed over time to detect the presence of a tone.
The present invention provides a tone detector that is fast, efficient and provides greater applicability to hearing devices than those known heretofore. Detection of tones is carried out by analysis of WOLA samples from WOLA subbands. Advantageously, the present invention does not calculate the phase of the input signal directly and therefore avoids the need for processor intensive calculations such as calculations of arctangent. The present invention calculates the normalized cross-correlation, per bin, between a WOLA sample (sample of frequency bin) of a WOLA analysis frame at the current time and a WOLA sample from an older WOLA analysis frame in the same frequency bin. That is, each calculation of normalized cross-correlation is calculated from the complex time-frequency of a WOLA sample from a WOLA analysis frame at one particular time, which typically includes the most recent WOLA block received and a WOLA sample of the same frequency bin from a complex time-frequency WOLA analysis frame from another particular time span, which is typically a WOLA analysis frame from an earlier time that does not include the most recent WOLA block. The calculation performs a complex multiplication, followed by the division of the product by its magnitude, as noted in equation 1:
In selecting WOLA samples for carrying out the calculations in equation (1), Δ is typically chosen such that there is no overlap between the WOLA analysis frames in the time domain, (as overlap would have the potential to bias the correlation metric), but not so large that it could potentially delay the detection time. Choosing Δ such that the older WOLA analysis frame finishes before the current WOLA analysis frame starts is one currently preferred technique for selecting Δ, although other values for Δ may be implemented alternatively. In general, it is preferred (although not necessary) that the WOLA analysis frames are selected to that the samples selected from them for comparison calculations do not overlap in time, so that the old WOLA analysis frame finishes at least one time sample before the time samples used to generate the WOLA blocks for the current WOLA analysis frame.
Equation 1 can be written equivalently as equation (2) as follows:
Although equation (2) is equivalent to equation (1), equation (2) is much more complicated to calculate than equation (1), so it is not calculated by the present invention during use, but is presented here for illustrative purposes only. Equation (2) shows that the NormCorn(f) metric is effectively a complex value with unity magnitude and with phase equal to the phase difference between the WOLA samples from the two WOLA analysis frames. It is noted that a tone will have a fixed phase difference across WOLA samples. Therefore a tone (with just a small amount of noise), when processed as described herein, will result in normalized correlation values with consistent phase. The correlation measured by the correlation calculations described herein measure the correlation of a signal over time. The calculations are performed each on a subband of the input signal, comparing two different WOLA samples in the same subband that occur at different times. The measurement then determines how similar the two different WOLA samples are, i.e., their correlation value, to detect whether a tone is present in that particular subband for which the calculations are performed. The calculations can be performed similarly for each subband, each subband having its own cross-correlation computation. Iterations of the calculations, each for a pair of WOLA samples of a particular subband across multiple times can be calculated.
The complex results from the WOLA within each frequency subband represent the magnitude and phase of the signal in the frequency subband at a given point in time. These complex-valued results created for each WOLA analysis frame or block of data can be analyzed over time by comparison to one another (using NormCorr) to detect the presence of a tone, as already described. For example,
The complex results of the WOLA analysis for a subband vary over time depending upon how close the frequency of the signal being processed is to the subband frequency center. For example,
However, in both cases, it can be observed that the signal that is being analyzed is tonal. This is because the spacings 307 are all equal to one another in
As discussed in the previous section, a tone will have a fixed phase difference across frames, therefore a tone (with just a small amount of noise) will result in normalized correlation values with consistent phase, like those in plot 400 of
The average (complex) value over several WOLA samples for the tonal input in
The value of a is selected to be small, for example 0.02, but may vary over a large range of values, typically from about 0.01 to 1.0, but the range could be extended at either or both ends The preferred value may also vary depending upon the sampling rate of the time frames. As an alternative to being a decimal value as described, α could be implemented as a right shift if α is a negative power of two.
Once smoothing has been applied as in equation (3), a metric for detecting tonality can be calculated. Equation (4) shows the metric, which is simply the magnitude (absolute value) of the smoothed, normalized cross-correlation.
This metric can be compared to a predetermined threshold to decide whether a tone is present. In one embodiment, this threshold is chosen to be 0.6, although this value may vary. For example, a predetermined threshold value may be set to have a value selected from the range from 0 to 1, typically within the range from 0.2 to 0.8.
Approximation techniques can be used to still further increase the efficiency of tone detection processing according to an embodiment of the present invention. For example, the numerator of equation (1) can be implemented with efficient multiplies and additions, as shown in equations (5) and (6):
Rearranging gives:
The approximation for the denominator of equation (1) is more difficult to perform. As shown in equation (7) below, it is noted that a square root operation and a divide operation are required. In an embedded DSP processor, these operations are typically not supported directly in hardware or in the instruction set, so these operations can take many cycles each to execute. This compares poorly with the multiplies and adds required for the numerator, which are typically supported in hardware and take a single cycle to execute (or less where multiple multiply/add operations are available per instruction).
DSP processors usually support a logarithm base 2 (log 2) approximation which can be utilized to make the implementation more efficient. This approximation has several names, CSB (count sign bits), CLB (count leading bits) and LOG 2ABS (log2 approximation of absolute value) amongst others. The approximation usually executes in a single cycle and returns the number of leading sign bits for use in normalizing a fractional number to the magnitude range 0.5 to 1.0. In this case, we also need to account for the square root, but that is easily done by dividing the CSB result by 2 (i.e. shifting right by 1 bit) as shown in equation (8) below.
Depending on the implementation of CSB on the processor a further scaling value can be applied to the result to ensure that there is no bias in the error introduced to NormCorr. Although the error introduced here can be quite big, it will on average be zero. If the smoothing in equation (3) is slow enough, it will have minimal effect on the behavior of the algorithm. In at least one example, a scaling value of 0.02 was used.
After smoothing has been applied at event 504, a metric used for detecting whether tonality is present is calculated at event 506, such as by use of equation (4). The metric can then be compared to a predetermined threshold value at event 508 to determine whether or not tonality exists in the subband currently being processed. This processing can be carried out iteratively for continual monitoring, for the current subband as well as for all other subbands or subset of subbands.
Optionally, implementation of approximation techniques can be employed for calculation of normalized cross-correlation, as noted above. At event 510 the results of the comparison at event 508 determine whether or not a tone has been detected. If a tone has not been detected, then no changes are made to the current state of the feedback cancellation system based on the results of the comparison, see event 512. If a tone has been detected, then the WOLA samples used in calculating the metric are input to the feedback cancellation system in subsystem 140 for further processing to determine whether the tone is feedback or rather is a sound received from the environment. If the tone is determined to be from the environment, the feedback cancellation system will make no changes to its current state, based on this finding. If the tone is determined to be feedback, then the feedback cancellation system will make a change or changes to suppress the feedback tone. For example, the feedback cancellation system may reduce the gain of the signal in the subband where the tonal signal is detected to be feedback, and/or increase a cancellation adaptation rate to more rapidly cancel the feedback tone in the subband where detected. These actions can be carried out for a particular subband or for multiple subbands.
At event 516 the next block is selected for processing with the current block and the calculations resume for this new block pair at event 502.
The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to numbers used (e.g. amounts, temperature, etc.) but some experimental errors and deviations should be accounted for.
The response of the tone detector to a stimulus (signal) is shown in
Examples 2-10 show in
While the present invention has been described with reference to the specific embodiments thereof, it should be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the true spirit and scope of the invention. In addition, many modifications may be made to adapt a particular situation, material, composition of matter, process, process step or steps, to the objective, spirit and scope of the present invention. All such modifications are intended to be within the scope of the claims appended hereto.
This application International Application No. PCT/US2021/028989, filed Apr. 23, 2021. PCT/US2021/028989 is hereby incorporated herein, in its entirety, by reference thereto and to which application we claim priority under 35 USC § 119.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2021/028989 | 4/23/2021 | WO |
