Monitoring of speaker impedance to detect pressure applied between mobile device and ear

Information

  • Patent Grant
  • 9467776
  • Patent Number
    9,467,776
  • Date Filed
    Friday, March 15, 2013
    11 years ago
  • Date Issued
    Tuesday, October 11, 2016
    8 years ago
Abstract
Coupling between a user's ear and a speaker of a mobile device may be determined by measuring an impedance of the speaker. When the user presses the mobile device against the user's ear, the speaker impedance changes as a result of loading in the speaker's acoustic radiation impedance. The speaker impedance change may be correlated with the force applied by the user to the mobile device. The measured speaker impedance may be provided as feedback to an adaptive noise cancellation (ANC) algorithm to adjust the output at the speaker. For example, when the mobile device is removed from the user's ear, the ANC algorithm may be muted.
Description
FIELD OF THE DISCLOSURE

The instant disclosure relates to mobile devices. More specifically, this disclosure relates to audio output of mobile devices.


BACKGROUND

Mobile devices are carried by a user throughout most or all of a day. During the day, the user may encounter many different environments, each with a different background noise characteristic and other acoustic effects. Mobile devices employ noise cancelling to take into account the environmental changes and improve the user's experience while using the mobile device. However, the performance of noise cancelling systems vary with how closely a speaker of the mobile device is placed against the user's ear, because the coupling between the user's ear and the speaker varies with distance.


SUMMARY

An impedance of a speaker of a mobile device varies due to objects interfering with the speaker's acoustic radiation field. For example, when a user places the mobile device closer to the user's ear, the speaker impedance increases. The impedance of the speaker may be measured by the mobile device to determine a pressure applied by the user between the mobile device and the user's ear. The impedance may be applied to an adaptive noise cancellation (ANC) circuit to adjust processing of an audio signal for playback through the speaker. The changes in impedance vary proportionally to the pressure applied by the user to place the mobile device against his ear and thus vary proportionally to a distance between the speaker and the user's ear canal. In one example, the impedance of a speaker may range from 5 ohms to 11 ohms depending on the pressure applied between the speaker and the user's ear.


According to one embodiment, a method may include calculating an impedance of a speaker of a mobile device. The method may also include determining a force applied by a user of the mobile device that causes contact between the mobile device and the user based, at least in part, on the calculated impedance. In certain embodiments, the impedance is an acoustic radiation impedance.


The method may also include applying a voltage to the speaker, and measuring a current through the speaker, in which the step of calculating the impedance comprises calculating the impedance based at least in part on the applied voltage and the measured current; adjusting an adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force; receiving an audio signal from an error microphone, in which the step of adjusting the ANC algorithm comprises adjusting the ANC algorithm based, at least in part, on the error microphone audio signal; and/or linearizing an output of the speaker based, at least in part, on the calculated impedance.


According to another embodiment, an apparatus may include a speaker. The apparatus may also include an amplifier coupled to the speaker. The apparatus may further include a processor coupled to the amplifier. The processor may be configured to execute the steps comprising calculating an impedance of the speaker and determining an environmental load of the speaker based, at least in part, on the calculated impedance.


In certain embodiments, the apparatus may be a mobile device; the environmental load may be proportional to a force, applied by a user of the mobile device, that causes contact between the mobile device and the user; the amplifier may be configured to apply a voltage to the speaker and measure a current through the speaker, and the processor may be configured to calculate the impedance based, at least in part, on the applied voltage and the measured current; the processor may be a digital signal processor (DSP) and the digital signal processor may be configured to adjust an adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force; and/or the processor may be further configured to linearize an output of the speaker based, at least in part, on the calculated impedance.


The apparatus may also include an error microphone coupled to the digital signal processor, in which the digital signal processor is further configured to adjust the ANC algorithm based, at least in part, on an audio signal received from the error microphone


According to yet another embodiment, a computer program product includes a non-transitory computer readable medium comprising code to execute the steps comprising calculating an impedance of a speaker and determining an environmental load of the speaker based, at least in part, on the calculated impedance. In certain embodiments, the environmental load may be proportional to a force, applied by a user of the mobile device that causes contact between the mobile device and the user.


The medium may also include code to detect, based at least in part on the determined force, when the mobile device is removed from an ear of the user; code to adjust an adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force; and/or code to linearize an output of the speaker based, at least in part, on the calculated impedance.


The foregoing has outlined rather broadly certain features and technical advantages of embodiments of the present invention in order that the detailed description that follows may be better understood. Additional features and advantages will be described hereinafter that form the subject of the claims of the invention. It should be appreciated by those having ordinary skill in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same or similar purposes. It should also be realized by those having ordinary skill in the art that such equivalent constructions do not depart from the spirit and scope of the invention as set forth in the appended claims. Additional features will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended to limit the present invention.





BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosed system and methods, reference is now made to the following descriptions taken in conjunction with the accompanying drawings.



FIG. 1 is a cross-section illustrating a mobile device with speaker impedance monitoring according to one embodiment of the disclosure.



FIG. 2 is a block diagram illustrating speaker impedance monitoring according to one embodiment of the disclosure.



FIG. 3 is a graph illustrating speaker impedance over time based on various user placements of the mobile device according to one embodiment of the disclosure.



FIG. 4 is a block diagram illustrating a noise canceling system according to one embodiment of the disclosure.



FIG. 5 is a flow chart illustrating a method for adaptive noise cancellation (ANC) in a mobile device according to one embodiment of the disclosure.



FIG. 6 is a block diagram of an adaptive noise cancellation (ANC) circuit according to one embodiment of the disclosure.



FIG. 7 is a graph of a response against pressure applied between the mobile device and the user's ear according to one embodiment of the disclosure.



FIG. 8 is a graph of a response as a function of frequency for different levels of ear pressure according to one embodiment of the disclosure.



FIG. 9 is a flow chart illustrating a method for adapting adaptive noise cancellation algorithms based on ear pressure according to one embodiment of the disclosure.





DETAILED DESCRIPTION


FIG. 1 is a cross-section illustrating a mobile device with speaker impedance monitoring according to one embodiment of the disclosure. A mobile device 102 may be placed near a user's ear 160. The mobile device 102 may be, for example, a mobile phone, a tablet computer, a laptop computer, or a wireless earpiece. The mobile device 102 may include a speaker 104, such as a transducer, driven by an amplifier 122 of a circuit 120. The speaker 104 may generate an acoustic sound field 150 near the mobile device 102. The user's ear 160 translates the acoustic sound field 150 into recognizable sounds for the user. For example, the acoustic sound field 150 may include speech conversations occurring during a phone call, playback of a voice mail message, playback of ring tones, and/or playback of audio or video files. The amplifier 122 may receive audio signals from a processor 124 of the circuit 120, such as a digital signal processor (DSP).


The mobile device 102 may also include a near-speech microphone 136, an error microphone 134, and a reference microphone 132. Each of the microphones 132, 134, and 136 receive audible sounds fields and translate the acoustic sound fields into electrical signals for processing by the circuit 120. For example, the near-speech microphone 136 may receive speech during a conversation occurring during a phone call. In another example, the error microphone 134 may receive the acoustic sound field 150 generated by the speaker 104. In a further example, the reference microphone 132 may be positioned away from a typical position of a user's mouth and may measure an ambient acoustic environment.


One apparatus for measuring a speaker impedance includes a resistor for measuring current. FIG. 2 is a block diagram illustrating speaker impedance monitoring according to one embodiment of the disclosure. The speaker 104 may be coupled to a voltage source 202 of the amplifier 122. The speaker 104 may have an impedance 206 proportional to loading of the acoustic sound field 150. A resistor 204 may be coupled in series with the speaker 104, such that a current passing through the resistor 204 is proportional to a current passing through the speaker 104. A voltmeter 208 may be coupled in parallel with the resistor 204 to measure a voltage across the resistor 204. The current passing through the resistor 204, and thus the speaker 104, may be calculated by multiplying the resistance value of the resistor 204 with the measured voltage at the voltmeter 208. The current may be calculated by a processor, such as the processor 124. The impedance 206 of the speaker 104 may be calculated, by the processor 124, from the voltage value at the voltage source 202, the resistance value of the resistor 204, and the voltage across the resistor 204 measured by the voltmeter 208.


The voltage at the speaker 104, VT, may be calculated by dividing the voltage of the voltage source 202, VS, across the resistor 204 and the speaker 104 according to a voltage ladder. For example, the impedance 206, ZL, may be calculated from the current, I, through the resistor 204, and the value of the resistor 204, R.


Speaker impedance, ZL, varies with the pressure applied by the user to place the mobile device against the user's ear. FIG. 3 is a graph illustrating speaker impedance over time based on various user placements of the mobile device according to one embodiment of the disclosure. A graph 300 plots current on a y-axis 306 against time on an x-axis 304. The x-axis 304 is divided into time periods 312, 314, 316, and 318 illustrating different events determined by the speaker impedance. A current line 302 illustrates a baseline pressure applied during the time period 312. During the time period 314, the current line 302, and thus speaker impedance, increases proportional to increasing pressure applied by the user to place the mobile device against the user's ear. During time period 316, the user removes the mobile device from his/her ear resulting in a decrease in the current line 302, and thus speaker impedance. During a time period 318, the user places the mobile device on the user's cheek resulting in an increase in current, and thus speaker impedance.


A speaker impedance may be provided to an adaptive noise cancellation (ANC) system for adapting the noise control system. FIG. 4 is a block diagram illustrating a noise canceling system according to one embodiment of the disclosure. A circuit 420 may receive input from the microphones 132, 134, and 136. Analog values from the microphones 132, 134, and 136 may be converted by analog-to-digital converters (ADCs) 421A, 421B, and 421C. The ADCs 421A, 421B, and 421C may be part of the noise control system or may be built into the microphones 132, 134, and 136, respectively. In one embodiment, the microphones 132, 134, and 136 are digital microphones, and no ADCs are placed between the digital microphones and the circuit 420.


The circuit 420 may also receive input from the speaker 104, such as an impedance value of the speaker 104. The impedance value may be calculated by the amplifier 122 and output to an analog-to-digital converter 421D, which converts the impedance value to a digital value for ANC circuit 430. In one embodiment, the speaker impedance output by the amplifier 122 is a digital value, and no analog-to-digital converter is present.


The ANC circuit 430 may generate an anti-noise signal, which is provided to a combiner 426. The anti-noise signal may be adjusted according to a force, or distance, between the user's ear and the speaker 104. For example, the anti-noise signal may be disabled when the user removes the phone from the user's ear. The removal of the phone from the user's ear may be detected when the speaker impedance falls below a threshold value.


The combiner 426 combines the anti-noise signal from the ANC circuit 430 with sound from the near speech microphone 136, internal audio 426, and audio signals received wirelessly through an antenna 428 and processed by a radio frequency (RF) circuit 422. The internal audio 426 may be, for example, ringtones, audio files, and/or audio portions of video files. Audio signals received through the antenna 428 may be, for example, streamed analog or digital audio signals and/or telephone conversations. The combiner 426 provides a single signal to a digital-to-analog converter (DAC) 423. The DAC 423 converts the digital signal of the combiner 423 to an analog audio signal for amplification by the amplifier 122 and output at the speaker 104.



FIG. 5 is a flow chart illustrating a method for adaptive noise cancellation in a mobile device according to one embodiment of the disclosure. A method 500 begins at block 502 with calculating an impedance of a speaker. The speaker impedance may be calculated by monitoring a current through the speaker and calculating an impedance of the speaker based on a known voltage value driving the speaker. The current monitoring may be performed in real-time during playback of an audio signal, such as during a voice conversation or during playback of audio files.


At block 504, a force applied by the user between the mobile device and the user's ear may be determined from the calculated impedance. The impedance of the speaker is proportional to a loading of the speaker. Higher force applied by the user between the mobile device and the user's ear increases the load on the speaker, which appears as an increase in impedance of the speaker. The force applied by the user may be proportional to the distance between the speaker and the user's ear canal.


At block 506, an adaptive noise cancellation algorithm is adjusted based, at least in part, on the determined force at block 504. For example, a control oversight algorithm may determine from the determined force that the user has removed the mobile device from the user's ear. When the off-ear condition is detected, the adaptive noise cancellation algorithm may be disabled. In another example, feedback regarding the speaker impedance may be provided to an adaptive noise cancellation algorithm to adjust the output of a speaker to compensate for the user's ear position. For example, output to the speaker may be adjusted to obtain linearization of the speaker audio output at high sound pressure levels (SPLs).


Additional details regarding the adaptive noise cancellation circuit are illustrated in FIG. 6. FIG. 6 is a block diagram of an adaptive noise cancellation circuit according to one embodiment of the disclosure. An adaptive filter 630 may be formed from a fixed filter 632A, having a response WFIXED(z), and an adaptive portion 632B, having a response WADAPT(z) with outputs summed by a combiner 636B. The adaptive filter 630 may receive the reference microphone signal ref and may adapt a transfer function W(z)=WFIXED(z)+WADAPT(z) to generate an anti-noise signal, which is provided to the combiner 426 that combines the anti-noise signal with the audio to be reproduced by the speaker. The response W(z) adapts to estimate a ratio P(z)/S(z), where S(z) is the response for an electro-acoustic path and P(z) is the response for an acoustic path. A controllable amplifier circuit 611 mutes or attenuates the anti-noise signal under certain non-ideal conditions, such as when the anti-noise signal is expected to be ineffective or erroneous due to lack of a seal between the user's ear and mobile device.


The coefficients of adaptive filter 632B may be controlled by a W coefficient control block 631, which may use a correlation of two signals to determine the response of the adaptive filter 632B to reduce the energy of the error, such as calculated by a least-mean square function, between the components of the reference microphone signal ref that are present in the error microphone signal err. The signals compared by the W coefficient control block 631 may be the reference microphone signal ref as shaped by a copy of an estimate SECOPY(z) of the response of path S(z) provided by filter 634B and an error signal e(n) formed by subtracting a modified portion of a downlink audio signal ds from the error microphone signal err. By transforming the reference microphone signal ref with a copy of the estimate of the response of path S(z), SECOPY(z), and adapting the adaptive filter 632B to reduce the correlation between the resultant signal and the error microphone signal err, the adaptive filter 632B adapts to the desired response of P(z)/S(z)−WFIXED(z). Thus, response W(z) adapts to P(z)/S(z), resulting in a noise-cancelling error, which may be for example white noise.


The signal compared to the output of the filter 634B by the W coefficient control block 631 adds to the error microphone signal err an inverted amount of the downlink audio signal ds that is processed by the filter response 634A, SE(z), of which response SECOPY(z) is a copy. By injecting an inverted amount of the downlink audio signal ds, the adaptive filter 632B may be prevented from adapting to the relatively large amount of downlink audio present in the error microphone signal err and by transforming that inverted copy of the downlink audio signal ds with the estimate of the response of path S(z). The downlink audio that is removed from the error microphone signal err before comparison may match the expected version of the downlink audio signal ds reproduced at the error microphone signal err, because the electrical and acoustical path of S(z) may be the path taken by the downlink audio signal ds to arrive at an error microphone. The filter 634B may have an adjustable response tuned to match the response of the adaptive filter 634A, such that the response of the filter 634B tracks the adapting of the adaptive filter 634A.


The adaptive filter 634A may include coefficients controlled by SE coefficient control block 633, which compares the downlink audio signal ds and the error microphone signal err after removal of the above-described filtered downlink audio signal ds that has been filtered by the adaptive filter 634A to represent the expected downlink audio delivered to an error microphone, and which has been removed from the output of the adaptive filter 634A by a combiner 636A. The SE coefficient control block 633 correlates the downlink speech signal ds with the components of downlink audio signal ds that are present in the error microphone signal err. The adaptive filter 634A is adapted to generate a signal from the downlink audio signal ds, and optionally the anti-noise signal combined by the combiner 636B during muting conditions, that when subtracted from the error microphone signal err, contains the content of error microphone signal err that is not due to the downlink audio signal ds. The overall energy of the error signal normalized to the overall energy of the response SE(z) is related to the pressure between the user's ear and mobile device, which may be determined by calculating the speaker impedance described above with reference to FIG. 5.


In one embodiment, an ear pressure indicator 637 may determine the ratio between E|e(N)|, which is the energy of the error signal generated by the combiner 636A and an overall magnitude of the response of SE(z): Σ|SEn(z)|. Ear pressure indication E|e(n)|/Σ|SEn(z)| may be only one example function of e(n) and SEn(z) that may be used to yield a measure of ear pressure. For example, Σ|SEn(z)| or ΣSEn(z)^2, which are a function of only SE(z) may be alternatively used, because the response SE(z) changes with ear pressure.


In another embodiment, the ear pressure indicator 637 may receive the speaker impedance measurement and calculate an ear pressure based, at least in part, on the speaker impedance. As described above with reference to FIG. 3, the speaker impedance may be used to determine a force applied by the user between the mobile device and the user's ear. That force may be entered into an algorithm to determine ear pressure. The ear pressure indicator 637 may implement calculation of ear pressure based on the speaker impedance, the error signal, and/or SE(z).


The ear pressure indicator 637 may output a value, either digital or analog, proportional to the force applied by the user between the mobile device and the user's ear. A comparator 642 compares the output of the ear pressure indicator 637 with a first, low pressure, threshold Vth,L. If the output is below the threshold, indicating that ear pressure is below the normal operating range, such as when the mobile device is off the user's ear, then the ear pressure response logic 638 may be signaled to take action to prevent generation of undesirable anti-noise at the user's ear. Similarly, a comparator 644 compares the output of the ear pressure indicator 637 with a second, high pressure, threshold Vth,H, and if E|e(n)|/Σ|SEn(z)| is above the threshold, indicating that ear pressure is above the normal operating range, such as when the mobile device is pressed hard onto the user's ear, then the ear pressure response logic 638 may be signaled to take action to prevent generation of undesirable anti-noise at the user's ear.



FIG. 7 is a graph of a response against force between the mobile device and the user's ear according to one embodiment of the disclosure. As pressure increases between a mobile device and the user's ear, the response SE(z) increases in magnitude, which indicates an improved electro-acoustic path S(z), which is a measure of a degree of coupling between the speaker and the error microphone. A higher degree of coupling between the user's ear and the speaker is indicated when response SE(z) increases in magnitude, and conversely, a lower degree of coupling between the user's ear and the speaker is indicated when response SE(z) decreases in magnitude. Because the adaptive filter 632B of FIG. 6 adapts to the desired response of P(z)/S(z), as ear pressure is increased and response SE(z) increases in energy, less anti-noise is generated. Conversely, as the pressure between the ear and mobile device decreases, the anti-noise signal may increase in energy, because the user's ear is no longer highly coupled to the speaker and/or the error microphone.



FIG. 8 is a graph of response SE(z) as a function of frequency for different levels of ear pressure according to one embodiment of the disclosure. As illustrated in FIG. 7, as the pressure is increased between the mobile device and the user's ear, the response SE(z) increases in magnitude in the middle frequency ranges of the graph, which correspond to frequencies at which most of the energy for speech is located. The graphs shown in FIGS. 7 and 8 may be determined for individual mobile device designs using either a computer model, or a mock-up of a simulated user's head that allows adjustment of contact pressure between the user's ear and mobile device, which may also have a measurement microphone in simulated ear canal.


In general, ANC operates properly when the user's ear is coupled to the speaker. Because the speaker may be able to only generate a certain output level, such as 80 dB sound pressure level (SPL) in a closed cavity, once the mobile device is no longer in contact with the user's ear, the anti-noise signal may be ineffective and muted. At high coupling between the user's ear and the mobile device, such as when a large force is applied between the mobile device and the user's ear, the higher-frequency energy, such as between 2 kHz and 5 kHz, may be attenuated, which may cause noise boost due to response W(z) not adapting to the attenuated condition of the higher frequencies. When the ear pressure is increased, the anti-noise signal may not be adapted to cancel energies at the higher frequencies. The response WADAPT(z) may then be reset to a predetermined value, and adaptation of response WADAPT(z) may be frozen, such as by holding the coefficients of response WADAPT(z) at constant predetermined values. Alternatively, the overall level of the anti-noise signal may be attenuated, or a leakage of response WADAPT(z) of the adaptive filter 632B may be increased. Leakage of response WADAPT(z) of the adaptive filter 632B may be provided by having the coefficients of response WADAPT(z) return to a flat frequency response or a fixed frequency response.


Referring back to FIG. 6, when the comparator 642 indicates that the degree of coupling between the user's ear and mobile device has been reduced below a first, low pressure, threshold, the ear pressure response logic 638 may stop adaptation of the W coefficient control 631, and the amplifier 611 may be disabled to mute the anti-noise signal. When the comparator 644 indicates that the coupling between the user's ear and the mobile device has increased above a second, high pressure, threshold, the ear pressure logic 638 may increase leakage of the W coefficient control 631 or reset response WADAPT(z) and freeze adaptation of response WADAPT(z).


Alternatively, the ear pressure indicator 637 may be a multi-valued or continuous indication of different ear pressure levels, and the actions above may be replaced by applying an attenuation factor to the anti-noise signal in conformity with the level of ear pressure, so that when the ear pressure passes out of the normal operating range, between the first threshold and the second threshold, the anti-noise signal level is also attenuated by lowering the gain of the amplifier 611.


In one embodiment, the response WFIXED(z) of the fixed filter 632A may be trained for high ear pressure. Then, the adaptive response of the adaptive filter 632B, response WADAPT(z), may be allowed to vary with ear pressure changes, up to the point that contact with the ear is minimal, at which point the adapting of response W(z) may be halted and the anti-noise signal may be muted, or the pressure on the ear is over a high threshold, at which time response WADAPT(z) may be reset and adaptation of response WADAPT(z) may be frozen, or the leakage may be increased. Additional details regarding ANC operation are disclosed in U.S. patent application Ser. No. 13/310,380 entitled “Ear-Coupling Detection and Adjustment of Adaptive Response in Noise-Canceling in Personal Audio Devices,” which is hereby incorporated by reference.



FIG. 9 is a flow chart illustrating a method for adapting adaptive noise cancellation algorithms based on ear pressure according to one embodiment of the disclosure. A method 900 begins at block 970 with computing an ear pressure indication from at least one of the error microphone signal, the SE(z) coefficients, and/or the speaker impedance. At block 972, it is determined if the ear pressure is lower than a first threshold. If so, an off-ear event is detected, and the method 900 continues to block 974 to stop adapting response W(z) and/or mute the anti-noise signal. If not, the method 900 continues to block 976.


At block 976, it is determined whether the ear pressure is above a second threshold, higher than the first threshold. If so a hard-pressure event is detected, and the method 900 continues to block 978 to increase leakage of the response W(z) and/or reset and freeze the adaptive portion of response W(z). If not, then normal operation is continued at block 980, during which response W(z) adapts to the ambient audio environment and the anti-noise signal is output to the speaker.


At block 982, it is determined whether the ANC is terminated or the mobile device is shut down. If not, then the method 900 repeats, such as by returning to block 970 and repeating blocks 972 and/or 976. If the determination is yes at block 982, then the method 900 terminates.


If implemented in firmware and/or software, the functions described above may be stored as one or more instructions or code on a computer-readable medium. Examples include non-transitory computer-readable media encoded with a data structure and computer-readable media encoded with a computer program. Computer-readable media includes physical computer storage media. A storage medium may be any available medium that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Disk and disc includes compact discs (CD), laser discs, optical discs, digital versatile discs (DVD), floppy disks and blu-ray discs. Generally, disks reproduce data magnetically, and discs reproduce data optically. Combinations of the above should also be included within the scope of computer-readable media.


In addition to storage on computer readable medium, instructions and/or data may be provided as signals on transmission media included in a communication apparatus. For example, a communication apparatus may include a transceiver having signals indicative of instructions and data. The instructions and data are configured to cause one or more processors to implement the functions outlined in the claims.


Although the present disclosure and certain representative advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the disclosure as defined by the appended claims. Moreover, the scope of the present application is not intended to be limited to the particular embodiments of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. As one of ordinary skill in the art will readily appreciate from the present disclosure, processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.

Claims
  • 1. A method, comprising: calculating an impedance of a speaker of a mobile device;determining a force, applied by a user of the mobile device, that causes contact between the mobile device and the user based, at least in part, on the calculated impedance, wherein the determined force is proportional to a distance between the speaker and a user's ear;adjusting an adaptive filter of an adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force in proportion to the distance between the speaker and the user's ear; andapplying the adaptive noise cancellation (ANC) algorithm to an audio output of the mobile device,wherein the step of adjusting the adaptive filter of the ANC algorithm comprises: based on an amount of the determined force, determining that contact is lost between the mobile device and the user and disabling application of the ANC algorithm to the audio output; andbased on another amount of the determined force, decreasing a magnitude of the ANC algorithm.
  • 2. The method of claim 1, in which the impedance is an acoustic radiation impedance.
  • 3. The method of claim 1, further comprising: applying a voltage to the speaker; andmeasuring a current through the speaker,in which the step of calculating the impedance comprises calculating the impedance based at least in part on the applied voltage and the measured current.
  • 4. The method of claim 1, further comprising receiving an audio signal from an error microphone, in which the step of adjusting the ANC algorithm comprises adjusting the ANC algorithm based, at least in part, on the error microphone audio signal.
  • 5. The method of claim 1, further comprising linearizing an output of the speaker based, at least in part, on the calculated impedance.
  • 6. The method of claim 1, wherein the step of adjusting the ANC algorithm comprises when the determined force is less than a threshold, stopping application of the ANC algorithm to the audio output.
  • 7. The method of claim 1, wherein the step of adjusting the ANC algorithm comprises when the determined force is greater than a threshold, increasing leakage of the adaptive filter of the ANC algorithm.
  • 8. The method of claim 1, further comprising adjusting the ANC algorithm by holding the coefficients of the adaptive filter at constant predetermined values when the determined force is greater than a threshold.
  • 9. The method of claim 1, further comprising applying a fixed filter of the ANC algorithm, wherein the fixed filter is trained for high ear pressure.
  • 10. An apparatus, comprising: a transducer;an amplifier coupled to the transducer;a processor coupled to the amplifier, in which the processor is configured to execute the steps comprising: calculating an impedance of the transducer;determining an environmental load of the transducer based, at least in part, on the calculated impedance, in which the environmental load is proportional to a force, applied by a user of the apparatus, that causes contact between the apparatus and the user, wherein the force is proportional to a distance between the speaker and a user's ear;adjusting an adaptive filter of an adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force in proportion to the distance between the speaker and the user's ear;applying the adaptive noise cancellation (ANC) algorithm to an audio output of the transducer;detecting, based at least in part on an amount of the determined force, when the apparatus is removed from an ear of the user and disabling application of the ANC algorithm to the audio output; anddecreasing a magnitude of the ANC algorithm based, at least in part, on another amount of the determined force.
  • 11. The apparatus of claim 10, in which the apparatus is a mobile device.
  • 12. The apparatus of claim 10, in which the amplifier is configured to: apply a voltage to the transducer; andmeasure a current through the transducer, andin which the processor is configured to: calculate the impedance based, at least in part, on the applied voltage and the measured current.
  • 13. The apparatus of claim 10, in which the processor is a digital signal processor (DSP) and the digital signal processor is configured to adjust the adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force.
  • 14. The apparatus of claim 13, further comprising: an error microphone coupled to the digital signal processor,in which the digital signal processor is further configured to adjust the ANC algorithm based, at least in part, on an audio signal received from the error microphone.
  • 15. The apparatus of claim 10, in which the processor is further configured to linearize an output of the transducer based, at least in part, on the calculated impedance.
  • 16. The apparatus of claim 10, wherein the processor is configured to stop application of the ANC algorithm when the determined force is less than a threshold.
  • 17. The apparatus of claim 10, wherein the processor is configured to increase a leakage of the adaptive filter of the ANC algorithm when the determined force is greater than a threshold.
  • 18. The apparatus of claim 10, wherein the processor is further configured to perform steps comprising adjusting the ANC algorithm by holding the coefficients of the adaptive filter at constant predetermined values when the determined force is greater than a threshold.
  • 19. The apparatus of claim 10, wherein the processor is further configured to perform steps comprising applying a fixed filter of the ANC algorithm, wherein the fixed filter is trained for high ear pressure.
  • 20. A computer program product, comprising: a non-transitory computer readable medium comprising code to execute the steps comprising: calculating an impedance of a speaker;determining a force, applied by a user of a mobile device, that causes contact between the mobile device and the user based, at least in part, on the calculated impedance, wherein the determined force is proportional to a distance between the speaker and a user's ear;adjusting an adaptive filter of an adaptive noise cancellation (ANC) algorithm based, at least in part, on the determined force in proportion to the distance between the speaker and the user's ear; andapplying the adaptive noise cancellation (ANC) algorithm to an audio output of the mobile device,wherein the step of adjusting the adaptive filter of the ANC algorithm comprises: based on an amount of the determined force, determining that contact is lost between the mobile device and the user and disabling application of the ANC algorithm to the audio output; andbased on another amount of the determined force, decreasing a magnitude of the ANC algorithm.
  • 21. The computer program product of claim 20, in which the medium further comprises code to linearize an output of the speaker based, at least in part, on the calculated impedance.
  • 22. The computer program product of claim 20, wherein the step of adjusting the ANC algorithm comprises when the determined force is less than a threshold, stopping application of the ANC algorithm to the audio output.
  • 23. The computer program product of claim 20, wherein the step of adjusting the ANC algorithm comprises when the determined force is greater than a threshold, increasing leakage of the adaptive filter of the ANC algorithm.
  • 24. The computer program product of claim 20, wherein the medium further comprises code to perform steps comprising adjusting the ANC algorithm by holding the coefficients of the adaptive filter at constant predetermined values when the determined force is greater than a threshold.
  • 25. The computer program product of claim 20, wherein the medium further comprises code to perform steps comprising applying a fixed filter of the ANC algorithm, wherein the fixed filter is trained for high ear pressure.
US Referenced Citations (203)
Number Name Date Kind
5044373 Northeved et al. Sep 1991 A
5251263 Andrea et al. Oct 1993 A
5278913 Delfosse et al. Jan 1994 A
5321759 Yuan Jun 1994 A
5337365 Hamabe et al. Aug 1994 A
5359662 Yuan et al. Oct 1994 A
5410605 Sawada et al. Apr 1995 A
5425105 Lo et al. Jun 1995 A
5445517 Kondou et al. Aug 1995 A
5465413 Enge et al. Nov 1995 A
5548681 Gleaves et al. Aug 1996 A
5586190 Trantow et al. Dec 1996 A
5640450 Watanabe Jun 1997 A
5699437 Finn Dec 1997 A
5706344 Finn Jan 1998 A
5740256 Castello Da Costa et al. Apr 1998 A
5768124 Stothers et al. Jun 1998 A
5815582 Claybaugh et al. Sep 1998 A
5832095 Daniels Nov 1998 A
5946391 Dragwidge et al. Aug 1999 A
5991418 Kuo Nov 1999 A
6041126 Terai et al. Mar 2000 A
6118878 Jones Sep 2000 A
6219427 Kates et al. Apr 2001 B1
6278786 McIntosh Aug 2001 B1
6282176 Hemkumar Aug 2001 B1
6418228 Terai et al. Jul 2002 B1
6434246 Kates et al. Aug 2002 B1
6434247 Kates et al. Aug 2002 B1
6522746 Marchok et al. Feb 2003 B1
6683960 Fujii et al. Jan 2004 B1
6766292 Chandran et al. Jul 2004 B1
6768795 Feltstrom et al. Jul 2004 B2
6850617 Weigand Feb 2005 B1
6940982 Watkins Sep 2005 B1
7058463 Ruha et al. Jun 2006 B1
7103188 Jones Sep 2006 B1
7181030 Rasmussen et al. Feb 2007 B2
7330739 Somayajula Feb 2008 B2
7365669 Melanson Apr 2008 B1
7680456 Muhammad et al. Mar 2010 B2
7742790 Konchitsky et al. Jun 2010 B2
7817808 Konchitsky et al. Oct 2010 B2
8019050 Mactavish et al. Sep 2011 B2
D666169 Tucker et al. Aug 2012 S
8249262 Chua et al. Aug 2012 B2
8251903 LeBoeuf et al. Aug 2012 B2
8290537 Lee et al. Oct 2012 B2
8325934 Kuo Dec 2012 B2
8379884 Horibe et al. Feb 2013 B2
8401200 Tiscareno et al. Mar 2013 B2
8442251 Jensen et al. May 2013 B2
8526627 Asao et al. Sep 2013 B2
8848936 Kwatra et al. Sep 2014 B2
8907829 Naderi Dec 2014 B1
8908877 Abdollahzadeh Milani et al. Dec 2014 B2
8948407 Alderson et al. Feb 2015 B2
8958571 Kwatra et al. Feb 2015 B2
20010053228 Jones Dec 2001 A1
20020003887 Zhang et al. Jan 2002 A1
20030063759 Brennan et al. Apr 2003 A1
20030185403 Sibbald Oct 2003 A1
20040047464 Yu et al. Mar 2004 A1
20040165736 Hetherington et al. Aug 2004 A1
20040167777 Hetherington et al. Aug 2004 A1
20040202333 Csermak et al. Oct 2004 A1
20040264706 Ray et al. Dec 2004 A1
20050004796 Trump et al. Jan 2005 A1
20050018862 Fisher Jan 2005 A1
20050117754 Sakawaki Jun 2005 A1
20050207585 Christoph Sep 2005 A1
20050240401 Ebenezer Oct 2005 A1
20060035593 Leeds Feb 2006 A1
20060069556 Nadjar et al. Mar 2006 A1
20060153400 Fujita et al. Jul 2006 A1
20070030989 Kates Feb 2007 A1
20070033029 Sakawaki Feb 2007 A1
20070038441 Inoue et al. Feb 2007 A1
20070047742 Taenzer et al. Mar 2007 A1
20070053524 Haulick et al. Mar 2007 A1
20070076896 Hosaka et al. Apr 2007 A1
20070154031 Avendano et al. Jul 2007 A1
20070258597 Rasmussen et al. Nov 2007 A1
20070297620 Choy Dec 2007 A1
20070297634 Hansson Dec 2007 A1
20080019548 Avendano Jan 2008 A1
20080101589 Horowitz et al. May 2008 A1
20080107281 Togami et al. May 2008 A1
20080144853 Sommerfeldt et al. Jun 2008 A1
20080177532 Greiss et al. Jul 2008 A1
20080181422 Christoph Jul 2008 A1
20080226098 Haulick et al. Sep 2008 A1
20080240455 Inoue et al. Oct 2008 A1
20080240457 Inoue et al. Oct 2008 A1
20090012783 Klein Jan 2009 A1
20090034748 Sibbald Feb 2009 A1
20090041260 Jorgensen et al. Feb 2009 A1
20090046867 Clemow Feb 2009 A1
20090060222 Jeong et al. Mar 2009 A1
20090080670 Solbeck et al. Mar 2009 A1
20090086990 Christoph Apr 2009 A1
20090175466 Elko et al. Jul 2009 A1
20090196429 Ramakrishnan et al. Aug 2009 A1
20090220107 Every et al. Sep 2009 A1
20090238369 Ramakrishnan et al. Sep 2009 A1
20090245529 Asada et al. Oct 2009 A1
20090254340 Sun et al. Oct 2009 A1
20090290718 Kahn et al. Nov 2009 A1
20090296965 Kojima Dec 2009 A1
20090304200 Kim et al. Dec 2009 A1
20090311979 Husted et al. Dec 2009 A1
20100014683 Maeda et al. Jan 2010 A1
20100014685 Wurm Jan 2010 A1
20100040245 Buil et al. Feb 2010 A1
20100061564 Clemow et al. Mar 2010 A1
20100069114 Lee et al. Mar 2010 A1
20100082339 Konchitsky et al. Apr 2010 A1
20100098263 Pan et al. Apr 2010 A1
20100098265 Pan et al. Apr 2010 A1
20100124336 Shridhar et al. May 2010 A1
20100124337 Wertz et al. May 2010 A1
20100131269 Park et al. May 2010 A1
20100150367 Mizuno Jun 2010 A1
20100158330 Guissin et al. Jun 2010 A1
20100166203 Peissig et al. Jul 2010 A1
20100195838 Bright Aug 2010 A1
20100195844 Christoph et al. Aug 2010 A1
20100207317 Iwami et al. Aug 2010 A1
20100239126 Grafenberg et al. Sep 2010 A1
20100246855 Chen Sep 2010 A1
20100266137 Sibbald et al. Oct 2010 A1
20100272276 Carreras et al. Oct 2010 A1
20100272283 Carreras et al. Oct 2010 A1
20100274564 Bakalos et al. Oct 2010 A1
20100284546 DeBrunner et al. Nov 2010 A1
20100291891 Ridgers et al. Nov 2010 A1
20100296666 Lin Nov 2010 A1
20100296668 Lee et al. Nov 2010 A1
20100310086 Magrath et al. Dec 2010 A1
20100322430 Isberg Dec 2010 A1
20110007907 Park et al. Jan 2011 A1
20110106533 Yu May 2011 A1
20110116643 Tiscareno et al. May 2011 A1
20110129098 Delano et al. Jun 2011 A1
20110130176 Magrath et al. Jun 2011 A1
20110142247 Fellers et al. Jun 2011 A1
20110144984 Konchitsky Jun 2011 A1
20110158419 Theverapperuma et al. Jun 2011 A1
20110206214 Christoph et al. Aug 2011 A1
20110222698 Asao et al. Sep 2011 A1
20110249826 Van Leest Oct 2011 A1
20110288860 Schevciw et al. Nov 2011 A1
20110293103 Park et al. Dec 2011 A1
20110299695 Nicholson Dec 2011 A1
20110305347 Wurm Dec 2011 A1
20110317848 Ivanov et al. Dec 2011 A1
20120135787 Kusunoki et al. May 2012 A1
20120140917 Nicholson et al. Jun 2012 A1
20120140942 Loeda Jun 2012 A1
20120140943 Hendrix et al. Jun 2012 A1
20120148062 Scarlett et al. Jun 2012 A1
20120155666 Nair Jun 2012 A1
20120170766 Alves et al. Jul 2012 A1
20120207317 Abdollahzadeh Milani Aug 2012 A1
20120207319 Tsuchiya et al. Aug 2012 A1
20120215519 Park et al. Aug 2012 A1
20120250873 Bakalos et al. Oct 2012 A1
20120259626 Li et al. Oct 2012 A1
20120263317 Shin et al. Oct 2012 A1
20120281850 Hyatt Nov 2012 A1
20120300958 Klemmensen Nov 2012 A1
20120300960 Mackay et al. Nov 2012 A1
20120308021 Kwatra et al. Dec 2012 A1
20120308024 Alderson et al. Dec 2012 A1
20120308025 Hendrix et al. Dec 2012 A1
20120308026 Kamath et al. Dec 2012 A1
20120308027 Kwatra Dec 2012 A1
20120308028 Kwatra et al. Dec 2012 A1
20120310640 Kwatra et al. Dec 2012 A1
20130010982 Elko et al. Jan 2013 A1
20130083939 Fellers et al. Apr 2013 A1
20130243198 Van Rumpt Sep 2013 A1
20130243225 Yokota Sep 2013 A1
20130272539 Kim et al. Oct 2013 A1
20130287218 Alderson et al. Oct 2013 A1
20130287219 Hendrix et al. Oct 2013 A1
20130301842 Hendrix et al. Nov 2013 A1
20130301846 Alderson et al. Nov 2013 A1
20130301847 Alderson et al. Nov 2013 A1
20130301848 Zhou et al. Nov 2013 A1
20130301849 Alderson et al. Nov 2013 A1
20130343556 Bright Dec 2013 A1
20130343571 Rayala et al. Dec 2013 A1
20140044275 Goldstein et al. Feb 2014 A1
20140050332 Nielsen et al. Feb 2014 A1
20140086425 Jensen et al. Mar 2014 A1
20140177851 Kitazawa et al. Jun 2014 A1
20140211953 Alderson et al. Jul 2014 A1
20140270222 Hendrix et al. Sep 2014 A1
20140270223 Li et al. Sep 2014 A1
20140270224 Zhou et al. Sep 2014 A1
20150092953 Abdollahzadeh Milani et al. Apr 2015 A1
20150104032 Kwatra et al. Apr 2015 A1
Foreign Referenced Citations (21)
Number Date Country
102011013343 Sep 2012 DE
1880699 Jan 2008 EP
1947642 Jul 2008 EP
2133866 Dec 2009 EP
2216774 Aug 2010 EP
2395500 Dec 2011 EP
2395501 Dec 2011 EP
2401744 Nov 2004 GB
2455821 Jun 2009 GB
2455824 Jun 2009 GB
2455828 Jun 2009 GB
2484722 Apr 2012 GB
H06186985 Jul 1994 JP
03015074 Feb 2003 WO
03015275 Feb 2003 WO
2004009007 Jan 2004 WO
2004017303 Feb 2004 WO
2007007916 Jan 2007 WO
2007113487 Oct 2007 WO
2010117714 Oct 2010 WO
2012134874 Oct 2012 WO
Non-Patent Literature Citations (62)
Entry
Benet et al., Using infrared sensors for distance measurement in mobile roots, Robotics and Autonomous Systems, 2002, vol. 40, pp. 255-266.
Campbell, Mikey, “Apple looking into self-adjusting earbud headphones with noise cancellation tech”, Apple Insider, Jul. 4, 2013, pp. 1-10 (10 pages in pdf), downloaded on May 14, 2014 from http://appleinsider.com/articles/13/07/04/apple-looking-into-self-adjusting-earbud-headphones-with-noise-cancellation-tech.
Pfann, et al., “LMS Adaptive Filtering with Delta-Sigma Modulated Input Signals,” IEEE Signal Processing Letters, Apr. 1998, pp. 95-97, vol. 5, No. 4, IEEE Press, Piscataway, NJ.
Toochinda, et al. “A Single-Input Two-Output Feedback Formulation for ANC Problems,” Proceedings of the 2001 American Control Conference, Jun. 2001, pp. 923-928, vol. 2, Arlington, VA.
Kuo, et al., “Active Noise Control: A Tutorial Review,” Proceedings of the IEEE, Jun. 1999, pp. 943-973, vol. 87, No. 6, IEEE Press, Piscataway, NJ.
Johns, et al., “Continuous-Time LMS Adaptive Recursive Filters,” IEEE Transactions on Circuits and Systems, Jul. 1991, pp. 769-778, vol. 38, No. 7, IEEE Press, Piscataway, NJ.
Shoval, et al., “Comparison of DC Offset Effects in Four LMS Adaptive Algorithms,” IEEE Transactions on Circuits and Systems II: Analog and Digital Processing, Mar. 1995, pp. 176-185, vol. 42, Issue 3, IEEE Press, Piscataway, NJ.
Mali, Dilip, “Comparison of DC Offset Effects on LMS Algorithm and its Derivatives,” International Journal of Recent Trends in Engineering, May 2009, pp. 323-328, vol. 1, No. 1, Academy Publisher.
Kates, James M., “Principles of Digital Dynamic Range Compression,” Trends in Amplification, Spring 2005, pp. 45-76, vol. 9, No. 2, Sage Publications.
Gao, et al., “Adaptive Linearization of a Loudspeaker,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr. 14-71,1991, pp. 3589-3592, Toronto, Ontario, CA.
Silva, et al., “Convex Combination of Adaptive Filters With Different Tracking Capabilities,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr. 15-20, 2007, pp. III 925-928, vol. 3, Honolulu, HI, USA.
Akhtar, et al., “A Method for Online Secondary Path Modeling in Active Noise Control Systems,” IEEE International Symposium on Circuits and Systems, May 23-26, 2005, pp. 264-267, vol. 1, Kobe, Japan.
Davari, et al., “A New Online Secondary Path Modeling Method for Feedforward Active Noise Control Systems,” IEEE International Conference on Industrial Technology, Apr. 2008, pp. 1-6, Chengdu, China.
Lan, et al., “An Active Noise Control System Using Online Secondary Path Modeling With Reduced Auxiliary Noise,” IEEE Signal Processing Letters, Jan. 2002, pp. 16-18, vol. 9, Issue 1, IEEE Press, Piscataway, NJ.
Liu, et al., “Analysis of Online Secondary Path Modeling With Auxiliary Noise Scaled by Residual Noise Signal,” IEEE Transactions on Audio, Speech and Language Processing, Nov. 2010, pp. 1978-1993, vol. 18, Issue 8, IEEE Press, Piscataway, NJ.
Black, John W., “An Application of Side-Tone in Subjective Tests of Microphones and Headsets”, Project Report No. NM 001 064.01.20, Research Report of the U.S. Naval School of Aviation Medicine, Feb. 1, 1954, 12 pages (pp. 1-12 in pdf), Pensacola, FL, US.
Peters, Robert W., “The Effect of High-Pass and Low-Pass Filtering of Side-Tone Upon Speaker Intelligibility”, Project Report No. NM 001 064.01.25, Research Report of the U.S. Naval School of Aviation Medicine, Aug. 16, 1954, 13 pages (pp. 1-13 in pdf), Pensacola, FL, US.
Lane, et al., “Voice Level: Autophonic Scale, Perceived Loudness, and the Effects of Sidetone”, The Journal of the Acoustical Society of America, Feb. 1961, pp. 160-167, vol. 33, No. 2., Cambridge, MA, US.
Liu, et al., “Compensatory Responses to Loudness-shifted Voice Feedback During Production of Mandarin Speech”, Journal of the Acoustical Society of America, Oct. 2007, pp. 2405-2412, vol. 122, No. 4.
Paepcke, et al., “Yelling in the Hall: Using Sidetone to Address a Problem with Mobile Remote Presence Systems”, Symposium on User Interface Software and Technology, Oct. 16-19, 2011, 10 pages (pp. 1-10 in pdf), Santa Barbara, CA, US.
Therrien, et al., “Sensory Attenuation of Self-Produced Feedback: The Lombard Effect Revisited”, PLOS ONE, Nov. 2012, pp. 1-7, vol. 7, Issue 11, e49370, Ontario, Canada.
Abdollahzadeh Milani, et al., “On Maximum Achievable Noise Reduction in ANC Systems”,2010 IEEE International Conference on Acoustics Speech and Signal Processing, Mar. 14-19, 2010, pp. 349-352, Dallas, TX, US.
Cohen, Israel, “Noise Spectrum Estimation in Adverse Environments: Improved Minima Controlled Recursive Averaging”, IEEE Transactions on Speech and Audio Processing, Sep. 2003, pp. 1-11, vol. 11, Issue 5, Piscataway, NJ, US.
Ryan, et al., “Optimum Near-Field Performance of Microphone Arrays Subject to a Far-Field Beampattern Constraint”, J. Acoust. Soc. Am., Nov. 2000, pp. 2248-2255, 108 (5), Pt. 1, Ottawa, Ontario, Canada.
Cohen, et al., “Noise Estimation by Minima Controlled Recursive Averaging for Robust Speech Enhancement”, IEEE Signal Processing Letters, Jan. 2002, pp. 12-15, vol. 9, No. 1, Piscataway, NJ, US.
Martin, Rainer, “Noise Power Spectral Density Estimation Based on Optimal Smoothing and Minimum Statistics”, IEEE Transactions on Speech and Audio Processing, Jul. 2001, pp. 504-512, vol. 9, No. 5, Piscataway, NJ, US.
Martin, Rainer, “Spectral Subtraction Based on Minimum Statistics”, Signal Processing VII Theories and Applications, Proceedings of EUSIPCO-94, 7th European Signal Processing Conference, Sep. 13-16, 1994, pp. 1182-1185, vol. III, Edinburgh, Scotland, U.K.
Booij, et al., “Virtual sensors for local, three dimensional, broadband multiple-channel active noise control and the effects on the quiet zones”, Proceedings of the International Conference on Noise and Vibration Engineering, ISMA 2010, Sep. 20-22, 2010, pp. 151-166, Leuven.
Kuo, et al., “Residual noise shaping technique for active noise control systems”, J. Acoust. Soc. Am. 95 (3), Mar. 1994, pp. 1665-1668.
Lopez-Caudana, Edgar Omar, “Active Noise Cancellation: The Unwanted Signal and the Hybrid Solution”, Adaptive Filtering Applications, Dr. Lino Garcia (Ed.), Jul. 2011, pp. 49-84, ISBN: 978-953-307-306-4, InTech.
Senderowicz, et al., “Low-Voltage Double-Sampled Delta-Sigma Converters”, IEEE Journal on Solid-State Circuits, Dec. 1997, pp. 1907-1919, vol. 32, No. 12, Piscataway, NJ.
Hurst, et al., “An improved double sampling scheme for switched-capacitor delta-sigma modulators”, 1992 IEEE Int. Symp. on Circuits and Systems, May 10-13, 1992, vol. 3, pp. 1179-1182, San Diego, CA.
Parkins, John W., “Narrowband and broadband active control in an enclosure using the acoustic energy density” Acoustical Society of America, Jul. 2000, vol. 108, No. 1, pp. 192-203.
U.S. Appl. No. 14/101,777, Alderson et al.
U.S. Appl. No. 14/101,955, Alderson.
U.S. Appl. No. 13/896,526, Naderi.
U.S. Appl. No. 13/924,935, Hellman.
U.S. Appl. No. 13/968,013, Abdollahzadeh Milani et al.
U.S. Appl. No. 14/252,235, Lu et al.
U.S. Appl. No. 13/724,656, Lu et al.
U.S. Appl. No. 13/721,832, Lu et al.
U.S. Appl. No. 13/762,504, Abdollahzadeh Milani et al.
U.S. Appl. No. 14/210,537, Abdollahzadeh Milani et al.
U.S. Appl. No. 14/210,589, Abdollahzadeh Milani et al.
U.S. Appl. No. 14/228,322, Alderson et al.
U.S. Appl. No. 14/197,814, Kaller et al.
U.S. Appl. No. 14/029,159, Li et al.
U.S. Appl. No. 14/062,951, Zhou et al.
U.S. Appl. No. 13/968,007, Hendrix et al.
U.S. Appl. No. 13/794,931, Lu et al.
U.S. Appl. No. 13/794,979, Alderson et al.
U.S. Appl. No. 13/686,353, Hendrix et al.
Jin, et al. “A simultaneous equation method-based online secondary path modeling algorithm for active noise control”, Journal of Sound and Vibration, Apr. 25, 2007, pp. 455-474, vol. 303, No. 3-5, London, GB.
Erkelens, et al., “Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation”, IEEE Transactions on Audio Speech and Language Processing, Aug. 2008, pp. 1112-1123, vol. 16, No. 6, Piscataway, NJ, US.
Rao, et al., “A Novel Two State Single Channel Speech Enhancement Technique”, India Conference (INDICON) 2011 Annual IEEE, IEEE, Dec. 2011, 6 pages (pp. 1-6 in pdf), Piscataway, NJ, US.
Rangachari, et al., “A noise-estimation algorithm for highly non-stationary environments”, Speech Communication, Feb. 2006, pp. 220-231, vol. 48, No. 2. Elsevier Science Publishers.
Parkins, et al., “Narrowband and broadband active control in an enclosure using the acoustic energy density”, J. Acoust. Soc. Am. Jul. 2000, pp. 192-203, vol. 108, issue 1, US.
Feng, Jinwei et al., “A broadband self-tuning active noise equaliser”, Signal Processing, Elsevier Science Publishers B.V. Amsterdam, NL, vol. 62, No. 2, Oct. 1, 1997, pp. 251-256.
Zhang, Ming et al., “A Robust Online Secondary Path Modeling Method with Auxiliary Noise Power Scheduling Strategy and Norm Constraint Manipulation”, IEEE Transactions on Speech and Audio Processing, IEEE Service Center, New York, NY, vol. 11, No. 1, Jan. 1, 2003.
Lopez-Gaudana, Edgar et al., “A hybrid active noise cancelling with secondary path modeling”, 51st Midwest Symposium on Circuits and Systems, 2008, MWSCAS 2008, Aug. 10, 2008, pp. 277-280.
Widrow, B., et al., Adaptive Noice Cancelling; Principles and Applications, Proceedings of the IEEE, Dec. 1975, pp. 1692-1716, vol. 63, No. 13, IEEE, New York, NY, US.
Morgan, et al., A Delayless Subband Adaptive Filter Architecture, IEEE Transactions on Signal Processing, IEEE Service Center, Aug. 1995, pp. 1819-1829, vol. 43, No. 8, New York, NY, US.
Related Publications (1)
Number Date Country
20140270208 A1 Sep 2014 US