DETAILED ACTION
This action is in response to the communications filed 3/28/2025, claims 1-20 are pending and have been examined.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 3/28/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 7-11, 14-18 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pedersen et al, US Publication No. 2016/0183012 A1.
Regarding Claim 1, Pedersen et al teaches, an audio device (Title/Abstract) comprising: a microphone (FIG. 4A, Microphone HA-MIC); a speaker (Loudspeaker SPK); at least one processor coupled to the microphone and the speaker (Paragraph 3, “The application further relates to a data processing system comprising a processor and program code means for causing the processor to perform at least some of the steps of the method.”, Paragraph 114, “The ear canal microphone is configured to pick up sound in the residual volume and may be used to provide a real ear measurement of sound pressure level (SPL) (and thus contribute to an estimate of a current RECD-value). The ear canal microphone is electrically connected to a processor for determining RECD (RECD measurement), e.g. in the BTE-part, via electrical conductors (E-con). The ear canal microphone may form part of the ITE-part (see e.g. FIG. 4A) or may alternatively be a separate microphone (as indicated in FIG. 2).”); and a memory coupled to the at least one processor (FIG. 4A, Memory MEM), the memory storing instructions that, when executed by the at least one processor, causes the device to perform operations that include: receiving a microphone signal from the microphone (Paragraph 49, “In an embodiment, the hearing device comprises a forward or signal path between an input transducer (microphone system and/or direct electric input (e.g. a wireless receiver)) and an output transducer.”); applying a gain to the microphone signal to generate an adjusted microphone signal based on a hearing profile of a user (Paragraph 49, “In an embodiment, the signal processing unit is located in the forward path. In an embodiment, the signal processing unit is adapted to provide a frequency dependent gain according to a user's particular needs.”, Paragraph 32, “Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure.”), determining whether a correlation between the applied gain and a feedback path attenuation signal exceeds a feedback threshold (Paragraph 37, “In an embodiment, the control unit is configured to determine a current estimate of real ear to coupler difference in a frequency range below a predetermined threshold frequency f.sub.th from the current feedback path difference measure above said threshold frequency f.sub.th. In an embodiment, the threshold frequency is in the range from 1 kHz to 2 kHz, e.g. around 1.5 kHz. In an embodiment, the control unit is configured to determine a current estimate of real ear to coupler difference in a first frequency range from the current feedback path difference measure in a second frequency range. In an embodiment, the first and second frequency ranges have no overlap. In an embodiment, the frequencies of the first frequency range are lower than the frequencies of the second frequency range.”); and when the feedback threshold is exceeded, applying feedback management to an audio signal that is driving the speaker based on the hearing profile of the user (Paragraph 112, “The feedback path estimation unit (FBP-E) may e.g. comprise an adaptive filter controlled by a prediction error algorithm, e.g. an LMS (Least Means Squared) algorithm, in order to predict and cancel the part of the microphone signal that is caused by feedback from the output transducer (OT) of the hearing device. The prediction error algorithm uses a reference signal (e.g. the output signal u(n)) together with a signal originating from the microphone signal (e.g. feedback corrected signal e(n)) to find the setting of the adaptive filter that minimizes the prediction error when the reference signal is applied to the adaptive filter. In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”, Paragraph 32, “Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure.”), wherein the audio signal driving the speaker comprises the adjusted microphone signal (Paragraph 112, “In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”).
Regarding Claim 2, Pedersen et al teaches all the limitations of claim 1, and further teaches, wherein the audio device is a headphone (Paragraph 55, “In an embodiment, the hearing device comprises a listening device, e.g. a hearing aid, e.g. a hearing instrument, e.g. a hearing instrument adapted for being located at the ear or fully or partially in the ear canal of a user, e.g. a headset, an earphone, an ear protection device or a combination thereof. In an embodiment, the hearing device comprises a hearing aid for compensating a user's hearing impairment.”) and the hearing profile comprises an audiogram (Paragraph 32, “In an embodiment, the control unit is configured to determine updated processing parameters based on said current estimate of real ear to coupler difference. In an embodiment, such processing parameters comprise frequency dependent gains derived from real ear to coupler difference, e.g. using a fitting rationale. A fitting rationale (algorithm) is e.g. used by a hearing care professional (HCP, e.g. an audiologist) to determine a prescribed gain versus frequency for a particular hearing impairment and a particular person (ear/hearing aid). A fitting algorithm, such as NAL-RP, NAL-NL2 (National Acoustic Laboratories, Australia), DSL (National Centre for Audiology, Ontario, Canada), ASA (American Seniors Association), etc., is generally used for this purpose. Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure. In an embodiment, the hearing device comprises an algorithm for determining an appropriate prescribed gain from an estimated real-ear-to-coupler difference (RECD) or a table of corresponding values.”).
Regarding Claim 3, Pedersen et al teaches all the limitations of claim 1, and further teaches, wherein the feedback threshold is frequency dependent (Paragraph 117, “The present inventors have realized (as schematically indicated in FIG. 3B) that a feedback path measurement at a low frequency does not necessarily say anything about the amplification loss due to leakage. Instead it is proposed to use the feedback path measured at frequencies above a threshold frequency, f.sub.th, e.g. 1500 Hz, to predict leakage below the threshold frequency f.sub.th (the frequency ranges may however overlap).”).
Regarding Claim 4, Pedersen et al teaches all the limitations of claim 1, and further teaches, wherein applying feedback management includes engaging in decorrelation techniques, the decorrelation techniques including injecting a noise signal into the audio signal that is driving the speaker (Paragraph 112, “To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”, Paragraph 42, “Alternatively or additionally, the probe signal may comprise one or more of a sine sweep, uncorrelated noise (such as white noise or pink noise), and a speech signal (the latter, if the device has a built in speech syntheses unit).”).
Regarding Claim 7, Pedersen et al teaches all the limitations of claim 1, and further teaches, wherein applying feedback management includes applying adaptive feedback cancellation techniques, the adaptive feedback cancellation techniques including applying a filter to the audio signal based on the hearing profile of the user (Paragraph 112, “The feedback path estimation unit (FBP-E) may e.g. comprise an adaptive filter controlled by a prediction error algorithm, e.g. an LMS (Least Means Squared) algorithm, in order to predict and cancel the part of the microphone signal that is caused by feedback from the output transducer (OT) of the hearing device. The prediction error algorithm uses a reference signal (e.g. the output signal u(n)) together with a signal originating from the microphone signal (e.g. feedback corrected signal e(n)) to find the setting of the adaptive filter that minimizes the prediction error when the reference signal is applied to the adaptive filter. In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”).
Regarding Claim 8, Pedersen et al teaches an acoustic feedback management system for an audio device (Title/Abstract) comprising: a memory to store instructions (FIG. 4A, Memory MEM); and at least one processor to execute the instructions (Paragraph 3, “The application further relates to a data processing system comprising a processor and program code means for causing the processor to perform at least some of the steps of the method.”) to: receive a microphone signal from a microphone (Paragraph 114, “The ear canal microphone is configured to pick up sound in the residual volume and may be used to provide a real ear measurement of sound pressure level (SPL) (and thus contribute to an estimate of a current RECD-value). The ear canal microphone is electrically connected to a processor for determining RECD (RECD measurement), e.g. in the BTE-part, via electrical conductors (E-con). The ear canal microphone may form part of the ITE-part (see e.g. FIG. 4A) or may alternatively be a separate microphone (as indicated in FIG. 2).”, Paragraph 49, “In an embodiment, the hearing device comprises a forward or signal path between an input transducer (microphone system and/or direct electric input (e.g. a wireless receiver)) and an output transducer.”);
based on a hearing profile of a user, apply a gain to the microphone signal to generate an adjusted microphone signal (Paragraph 49, “In an embodiment, the signal processing unit is located in the forward path. In an embodiment, the signal processing unit is adapted to provide a frequency dependent gain according to a user's particular needs.”, Paragraph 32, “Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure.”);
determine whether a correlation between the applied gain and a feedback path attenuation signal exceeds a feedback threshold (Paragraph 37, “In an embodiment, the control unit is configured to determine a current estimate of real ear to coupler difference in a frequency range below a predetermined threshold frequency f.sub.th from the current feedback path difference measure above said threshold frequency f.sub.th. In an embodiment, the threshold frequency is in the range from 1 kHz to 2 kHz, e.g. around 1.5 kHz. In an embodiment, the control unit is configured to determine a current estimate of real ear to coupler difference in a first frequency range from the current feedback path difference measure in a second frequency range. In an embodiment, the first and second frequency ranges have no overlap. In an embodiment, the frequencies of the first frequency range are lower than the frequencies of the second frequency range.”);
and when the feedback threshold is exceeded, apply feedback management to an audio signal that is driving a speaker based on the hearing profile of the user (Paragraph 112, “The feedback path estimation unit (FBP-E) may e.g. comprise an adaptive filter controlled by a prediction error algorithm, e.g. an LMS (Least Means Squared) algorithm, in order to predict and cancel the part of the microphone signal that is caused by feedback from the output transducer (OT) of the hearing device. The prediction error algorithm uses a reference signal (e.g. the output signal u(n)) together with a signal originating from the microphone signal (e.g. feedback corrected signal e(n)) to find the setting of the adaptive filter that minimizes the prediction error when the reference signal is applied to the adaptive filter. In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”, Paragraph 32, “Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure.”), wherein the audio signal driving the speaker comprises the adjusted microphone signal (Paragraph 112, “In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”).
Regarding Claim 9, Pedersen et al teaches all the limitations of claim 8, and further teaches, wherein the audio device is a headphone (Paragraph 55, “In an embodiment, the hearing device comprises a listening device, e.g. a hearing aid, e.g. a hearing instrument, e.g. a hearing instrument adapted for being located at the ear or fully or partially in the ear canal of a user, e.g. a headset, an earphone, an ear protection device or a combination thereof. In an embodiment, the hearing device comprises a hearing aid for compensating a user's hearing impairment.”) and the hearing profile comprises an audiogram (Paragraph 32, “In an embodiment, the control unit is configured to determine updated processing parameters based on said current estimate of real ear to coupler difference. In an embodiment, such processing parameters comprise frequency dependent gains derived from real ear to coupler difference, e.g. using a fitting rationale. A fitting rationale (algorithm) is e.g. used by a hearing care professional (HCP, e.g. an audiologist) to determine a prescribed gain versus frequency for a particular hearing impairment and a particular person (ear/hearing aid). A fitting algorithm, such as NAL-RP, NAL-NL2 (National Acoustic Laboratories, Australia), DSL (National Centre for Audiology, Ontario, Canada), ASA (American Seniors Association), etc., is generally used for this purpose. Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure. In an embodiment, the hearing device comprises an algorithm for determining an appropriate prescribed gain from an estimated real-ear-to-coupler difference (RECD) or a table of corresponding values.”).
Regarding Claim 10, Pedersen et al teaches all the limitations of claim 8, and further teaches, wherein the feedback threshold is frequency dependent (Paragraph 117, “The present inventors have realized (as schematically indicated in FIG. 3B) that a feedback path measurement at a low frequency does not necessarily say anything about the amplification loss due to leakage. Instead it is proposed to use the feedback path measured at frequencies above a threshold frequency, f.sub.th, e.g. 1500 Hz, to predict leakage below the threshold frequency f.sub.th (the frequency ranges may however overlap).”).
Regarding Claim 11, Pedersen et al teaches all the limitations of claim 8, and further teaches, wherein the at least one processor executes the instructions to apply feedback management by engaging decorrelation techniques, the decorrelation techniques including injecting a noise signal into the audio signal that is driving the speaker (Paragraph 112, “To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”, Paragraph 42, “Alternatively or additionally, the probe signal may comprise one or more of a sine sweep, uncorrelated noise (such as white noise or pink noise), and a speech signal (the latter, if the device has a built in speech syntheses unit).”).
Regarding Claim 14, Pedersen et al teaches all the limitations of claim 8, and further teaches, wherein the at least one processor executes the instructions to apply feedback management by applying adaptive feedback cancellation techniques, the adaptive feedback cancellation techniques including applying a filter to the audio signal based on the hearing profile of the user (Paragraph 112, “The feedback path estimation unit (FBP-E) may e.g. comprise an adaptive filter controlled by a prediction error algorithm, e.g. an LMS (Least Means Squared) algorithm, in order to predict and cancel the part of the microphone signal that is caused by feedback from the output transducer (OT) of the hearing device. The prediction error algorithm uses a reference signal (e.g. the output signal u(n)) together with a signal originating from the microphone signal (e.g. feedback corrected signal e(n)) to find the setting of the adaptive filter that minimizes the prediction error when the reference signal is applied to the adaptive filter. In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”).
Regarding Claim 15, Pedersen et al teaches, a method for managing acoustic feedback for an audio device (Title/Abstract) comprising: receiving a microphone signal from a microphone (Paragraph 49, “In an embodiment, the hearing device comprises a forward or signal path between an input transducer (microphone system and/or direct electric input (e.g. a wireless receiver)) and an output transducer.”);
based on a hearing profile of a user, applying, by processing circuitry of the device, a gain to the microphone signal to generate an adjusted microphone signal (Paragraph 49, “In an embodiment, the signal processing unit is located in the forward path. In an embodiment, the signal processing unit is adapted to provide a frequency dependent gain according to a user's particular needs.”, Paragraph 32, “Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure.”);
determining, by the processing circuitry of the device, whether a correlation between the applied gain and a feedback path attenuation signal exceeds a feedback threshold (Paragraph 37, “In an embodiment, the control unit is configured to determine a current estimate of real ear to coupler difference in a frequency range below a predetermined threshold frequency f.sub.th from the current feedback path difference measure above said threshold frequency f.sub.th. In an embodiment, the threshold frequency is in the range from 1 kHz to 2 kHz, e.g. around 1.5 kHz. In an embodiment, the control unit is configured to determine a current estimate of real ear to coupler difference in a first frequency range from the current feedback path difference measure in a second frequency range. In an embodiment, the first and second frequency ranges have no overlap. In an embodiment, the frequencies of the first frequency range are lower than the frequencies of the second frequency range.”);
and when the feedback threshold is exceeded, applying, by the processing circuitry of the device, feedback management to an audio signal that is driving a speaker based on the hearing profile of the user (Paragraph 112, “The feedback path estimation unit (FBP-E) may e.g. comprise an adaptive filter controlled by a prediction error algorithm, e.g. an LMS (Least Means Squared) algorithm, in order to predict and cancel the part of the microphone signal that is caused by feedback from the output transducer (OT) of the hearing device. The prediction error algorithm uses a reference signal (e.g. the output signal u(n)) together with a signal originating from the microphone signal (e.g. feedback corrected signal e(n)) to find the setting of the adaptive filter that minimizes the prediction error when the reference signal is applied to the adaptive filter. In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”, Paragraph 32, “Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure.”), wherein the audio signal driving the speaker comprises the adjusted microphone signal (Paragraph 112, “In a normal mode of operation, the estimate of the feedback path vh(n) provided by the feedback estimation unit (FBP-E) is subtracted from the microphone signal y(n) in sum unit ‘+’ providing a so-called ‘error signal’ (or feedback-corrected signal e(n)), which is fed to the signal processing unit (SPU) and to the (algorithm part of the) the feedback estimation unit (FBP-E). To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”).
Regarding Claim 16, Pedersen et al teaches all the limitations of claim 15, and further teaches, wherein the audio device is a headphone (Paragraph 55, “In an embodiment, the hearing device comprises a listening device, e.g. a hearing aid, e.g. a hearing instrument, e.g. a hearing instrument adapted for being located at the ear or fully or partially in the ear canal of a user, e.g. a headset, an earphone, an ear protection device or a combination thereof. In an embodiment, the hearing device comprises a hearing aid for compensating a user's hearing impairment.”) and the hearing profile comprises an audiogram (Paragraph 32, “In an embodiment, the control unit is configured to determine updated processing parameters based on said current estimate of real ear to coupler difference. In an embodiment, such processing parameters comprise frequency dependent gains derived from real ear to coupler difference, e.g. using a fitting rationale. A fitting rationale (algorithm) is e.g. used by a hearing care professional (HCP, e.g. an audiologist) to determine a prescribed gain versus frequency for a particular hearing impairment and a particular person (ear/hearing aid). A fitting algorithm, such as NAL-RP, NAL-NL2 (National Acoustic Laboratories, Australia), DSL (National Centre for Audiology, Ontario, Canada), ASA (American Seniors Association), etc., is generally used for this purpose. Alternatively, other proprietary schemes can be used. Among the inputs to such fitting algorithms are a) data related to a user's hearing ability, such as hearing threshold or hearing loss data (e.g. based on an audiogram), and comfort level for the user in question, b) type of hearing aid, and c) real-ear-to-coupler difference (RECD) measure. In an embodiment, the hearing device comprises an algorithm for determining an appropriate prescribed gain from an estimated real-ear-to-coupler difference (RECD) or a table of corresponding values.”).
Regarding Claim 17, Pedersen et al teaches all the limitations of claim 15, and further teaches, wherein the feedback threshold is frequency dependent (Paragraph 117, “The present inventors have realized (as schematically indicated in FIG. 3B) that a feedback path measurement at a low frequency does not necessarily say anything about the amplification loss due to leakage. Instead it is proposed to use the feedback path measured at frequencies above a threshold frequency, f.sub.th, e.g. 1500 Hz, to predict leakage below the threshold frequency f.sub.th (the frequency ranges may however overlap).”).
Regarding Claim 18, Pedersen et al teaches all the limitations of claim 15, and further teaches, wherein applying feedback management includes engaging in decorrelation techniques, the decorrelation techniques including injecting a noise signal into the audio signal that is driving the speaker (Paragraph 112, “To provide an improved decorrelation between the output and input signal, it may be desirable to add the probe signal us(n) to the output signal. This probe signal can be used as the reference signal to the algorithm part of the adaptive filter, and/or it may be mixed with the ordinary output u′(n) of the signal processing unit (SPU) to form the reference signal u(n).”, Paragraph 42, “Alternatively or additionally, the probe signal may comprise one or more of a sine sweep, uncorrelated noise (such as white noise or pink noise), and a speech signal (the latter, if the device has a built in speech syntheses unit).”).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Pedersen et al, US Publication No. 2016/0183012 A1, in view of Wiinberg, WO 2022184394 A1.
Regarding Claim 5, Pedersen et al teaches all the limitations of claim 4, but does not further teach, wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold,
However, Wiinberg, in a similar invention in the same field of endeavor teaches, wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold (See Page 4, “A hearing aid system according to a first aspect of the invention comprises an acoustical-electrical input transducer configured to receive an audio input signal and to output an input transducer output signal, a first combiner, configured to subtract a feedback cancellation signal from the input transducer output signal and to hereby generate a residual signal, a digital signal processor configured to process the residual signal to generate a processed residual signal, an electrical-acoustical output transducer configured to receive an output transducer input signal and to generate an acoustical output transducer output signal, an adaptive feedback canceller configured to receive the residual signal and the output transducer input signal and to provide the feedback cancellation signal; a de-correlation unit configured to, when active, receive the processed residual signal and to frequency shift at least part of the processed residual signal and hereby provide a frequency shifted output transducer input signal, an artifact detector configured to determine if active operation of the de-correlation unit, in a current sound environment, will result in audible artifacts in the form of amplitude modulation due to mixing in the ear canal of a directly transmitted sound and the frequency shifted acoustical output transducer output signal, and a de-correlation controller configured to activate or de-activate the de-correlation unit dependent on whether the artifact detector determines that active operation of the de-correlation unit will result in audible artifacts.”, See Page 8, “Now the modulation frequency spectrum is provided to a modulation masking estimator 209 that compares at least one normalized level of a band pass filtered envelope signal, and with a corresponding modulation masking threshold level and in case said normalized level exceeds said modulation masking threshold level, estimates that operation of the de-correlation unit (210) to apply a frequency shift having a frequency within the frequency range of the band pass filtered envelope signal will not result in audible artifacts in the current sound environment, when the frequency shift is applied to a frequency range of the input transducer signal that corresponds to the frequency range of the band pass filtered frequency band signal that the band pass filtered envelope signal was based on.”, Describes the generation of a residual signal in decorrelation techniques, as well as the selection of frequency bands based upon a feedback threshold.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold, as taught by Wiinberg, with the system as taught by Pedersen et al. The motivation being that limiting the noise signal to frequencies in which the feedback is present allows for a more targeted noise processing, and reduce the amount of processing required.
Regarding Claim 12, Pedersen et al teaches all the limitations of claim 11, but does not further teach, wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold,
However, Wiinberg, in a similar invention in the same field of endeavor teaches, wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold (See Page 4, “A hearing aid system according to a first aspect of the invention comprises an acoustical-electrical input transducer configured to receive an audio input signal and to output an input transducer output signal, a first combiner, configured to subtract a feedback cancellation signal from the input transducer output signal and to hereby generate a residual signal, a digital signal processor configured to process the residual signal to generate a processed residual signal, an electrical-acoustical output transducer configured to receive an output transducer input signal and to generate an acoustical output transducer output signal, an adaptive feedback canceller configured to receive the residual signal and the output transducer input signal and to provide the feedback cancellation signal; a de-correlation unit configured to, when active, receive the processed residual signal and to frequency shift at least part of the processed residual signal and hereby provide a frequency shifted output transducer input signal, an artifact detector configured to determine if active operation of the de-correlation unit, in a current sound environment, will result in audible artifacts in the form of amplitude modulation due to mixing in the ear canal of a directly transmitted sound and the frequency shifted acoustical output transducer output signal, and a de-correlation controller configured to activate or de-activate the de-correlation unit dependent on whether the artifact detector determines that active operation of the de-correlation unit will result in audible artifacts.”, See Page 8, “Now the modulation frequency spectrum is provided to a modulation masking estimator 209 that compares at least one normalized level of a band pass filtered envelope signal, and with a corresponding modulation masking threshold level and in case said normalized level exceeds said modulation masking threshold level, estimates that operation of the de-correlation unit (210) to apply a frequency shift having a frequency within the frequency range of the band pass filtered envelope signal will not result in audible artifacts in the current sound environment, when the frequency shift is applied to a frequency range of the input transducer signal that corresponds to the frequency range of the band pass filtered frequency band signal that the band pass filtered envelope signal was based on.”, Describes the generation of a residual signal in decorrelation techniques, as well as the selection of frequency bands based upon a feedback threshold.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold, as taught by Wiinberg, with the system as taught by Pedersen et al. The motivation being that limiting the noise signal to frequencies in which the feedback is present allows for a more targeted noise processing, and reduce the amount of processing required.
Regarding Claim 19, Pedersen et al teaches all the limitations of claim 18, but does not further teach, wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold.
However, Wiinberg, in a similar invention in the same field of endeavor teaches, wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold (See Page 4, “A hearing aid system according to a first aspect of the invention comprises an acoustical-electrical input transducer configured to receive an audio input signal and to output an input transducer output signal, a first combiner, configured to subtract a feedback cancellation signal from the input transducer output signal and to hereby generate a residual signal, a digital signal processor configured to process the residual signal to generate a processed residual signal, an electrical-acoustical output transducer configured to receive an output transducer input signal and to generate an acoustical output transducer output signal, an adaptive feedback canceller configured to receive the residual signal and the output transducer input signal and to provide the feedback cancellation signal; a de-correlation unit configured to, when active, receive the processed residual signal and to frequency shift at least part of the processed residual signal and hereby provide a frequency shifted output transducer input signal, an artifact detector configured to determine if active operation of the de-correlation unit, in a current sound environment, will result in audible artifacts in the form of amplitude modulation due to mixing in the ear canal of a directly transmitted sound and the frequency shifted acoustical output transducer output signal, and a de-correlation controller configured to activate or de-activate the de-correlation unit dependent on whether the artifact detector determines that active operation of the de-correlation unit will result in audible artifacts.”, See Page 8, “Now the modulation frequency spectrum is provided to a modulation masking estimator 209 that compares at least one normalized level of a band pass filtered envelope signal, and with a corresponding modulation masking threshold level and in case said normalized level exceeds said modulation masking threshold level, estimates that operation of the de-correlation unit (210) to apply a frequency shift having a frequency within the frequency range of the band pass filtered envelope signal will not result in audible artifacts in the current sound environment, when the frequency shift is applied to a frequency range of the input transducer signal that corresponds to the frequency range of the band pass filtered frequency band signal that the band pass filtered envelope signal was based on.”, Describes the generation of a residual signal in decorrelation techniques, as well as the selection of frequency bands based upon a feedback threshold.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of wherein a frequency band of the noise signal is limited to a frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold, as taught by Wiinberg, with the system as taught by Pedersen et al. The motivation being that limiting the noise signal to frequencies in which the feedback is present allows for a more targeted noise processing, and reduce the amount of processing required.
Claims 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Pedersen et al, US Publication No. 2016/0183012 A1, in view of Wiinberg, WO 2022184394 A1, further in view of Anderson, US Publication No. 2017/0195803 A1.
Regarding Claim 6, Pedersen et al in view of Wiinberg teaches all the limitations of claim 5, but does not further teach, wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user,
However, Anderson, in a similar invention in the same field of endeavor teaches, wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user (Paragraph 132, “Synthetic frequency replacement processor 2540 can be configured to receive first signal 2530 and replace, supplant, overwrite, or superimpose upon, a portion of first signal 2530 within a band or range of frequencies where a user may have hearing ability, with a noise signal which is modulated by the volume envelope of a portion of first signal 2530 within a band or range of frequencies where a user may have hearing loss and then output a resulting output signal 2550 to speaker 2560. Furthermore, according to an embodiment, the noise signal can be boosted, lifted, weighted, or translated, if necessary, to exceed a user's threshold of hearing within a band or range of frequencies where a user may have hearing ability. Speaker 2560 can be configured to receive output signal 2550 and convert it to air conduction audio signal 2570 having improved speech intelligibility.” Displays the usage of volume/frequency control to allow for a generated noise signal to fall outside of the range of the user’s hearing ability.),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user, as taught by Anderson, with the system as taught by Pedersen et al, in view of Wiinberg. The motivation being to reduce the impact of the noise signal upon the audible portions of the sound signal, and allow for more user comfort.
Regarding Claim 13, Pedersen et al in view of Wiinberg teaches all the limitations of claim 12, but does not further teach, wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user,
However, Anderson, in a similar invention in the same field of endeavor teaches, wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user (Paragraph 132, “Synthetic frequency replacement processor 2540 can be configured to receive first signal 2530 and replace, supplant, overwrite, or superimpose upon, a portion of first signal 2530 within a band or range of frequencies where a user may have hearing ability, with a noise signal which is modulated by the volume envelope of a portion of first signal 2530 within a band or range of frequencies where a user may have hearing loss and then output a resulting output signal 2550 to speaker 2560. Furthermore, according to an embodiment, the noise signal can be boosted, lifted, weighted, or translated, if necessary, to exceed a user's threshold of hearing within a band or range of frequencies where a user may have hearing ability. Speaker 2560 can be configured to receive output signal 2550 and convert it to air conduction audio signal 2570 having improved speech intelligibility.” Displays the usage of volume/frequency control to allow for a generated noise signal to fall outside of the range of the user’s hearing ability.),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user, as taught by Anderson, with the system as taught by Pedersen et al, in view of Wiinberg. The motivation being to reduce the impact of the noise signal upon the audible portions of the sound signal, and allow for more user comfort.
Regarding Claim 20, Pedersen et al, in view of Wiinberg teaches all the limitations of claim 19, but does not further teach, wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user,
However, Anderson, in a similar invention in the same field of endeavor teaches, wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user (Paragraph 132, “Synthetic frequency replacement processor 2540 can be configured to receive first signal 2530 and replace, supplant, overwrite, or superimpose upon, a portion of first signal 2530 within a band or range of frequencies where a user may have hearing ability, with a noise signal which is modulated by the volume envelope of a portion of first signal 2530 within a band or range of frequencies where a user may have hearing loss and then output a resulting output signal 2550 to speaker 2560. Furthermore, according to an embodiment, the noise signal can be boosted, lifted, weighted, or translated, if necessary, to exceed a user's threshold of hearing within a band or range of frequencies where a user may have hearing ability. Speaker 2560 can be configured to receive output signal 2550 and convert it to air conduction audio signal 2570 having improved speech intelligibility.” Displays the usage of volume/frequency control to allow for a generated noise signal to fall outside of the range of the user’s hearing ability.),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of wherein a decibel level of the noise signal is below a detection threshold so that the noise signal is inaudible to the user, the detection threshold being based on the hearing profile of the user, as taught by Anderson, with the system as taught by Pedersen et al, in view of Wiinberg. The motivation being to reduce the impact of the noise signal upon the audible portions of the sound signal, and allow for more user comfort.
Conclusion
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/DYLAN MAGUIRE NEECE/ Examiner, Art Unit 2692
/CAROLYN R EDWARDS/ Supervisory Patent Examiner, Art Unit 2692
