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 .
DETAILED ACTION
Applicant is advised that the new art unit number is 2692. Please use the new art unit number for all future communications.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/8/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant's cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claim 1, 15 objected to because of the following informalities:
Claim 1, line 1: “configured be worn” should be --configured to be worn--.
Claim 15, line 1: “configured be worn” should be --configured to be worn--.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-5, 8, 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li et al. (CN 112565997 using an English machine translation).
Regarding claim 15, Li discloses a hearing device configured be worn at an ear of a user, the hearing device comprising:
an input transducer (Fig. 3: microphone) configured to provide an audio signal indicative of a sound detected in an environment of the user (Fig. 3 and page 14, lines 8-21);
a processor configured to process the audio signal by at least one audio processing algorithm to generate a processed audio signal (Fig. 3: black box between the microphone and speaker) (page 7, lines 4-15); and
an output transducer (Fig 3: speaker) configured to output an output audio signal based on the processed audio signal so as to stimulate the user's hearing (inherent function of a hearing aid speaker),
characterized in that the processor is further configured to
provide different audio processing algorithms each configured to be applied on the audio signal and associated with a performance index (MOS score) indicative of a performance of the audio processing algorithm when applied on the audio signal (page 16, lines 20-37);
determine a target index (4.0 points) relative to the performance index, the target index indicative of a target performance of said processing of the audio signal (page 16, lines 20-37);
select, depending on the target index, at least one of the processing algorithms (page 16, lines 20-37); and
apply the selected processing algorithm on the audio signal (page 17, lines 9-18).
Claim 1 recites similar limitations as claim 15, and is rejected for the same reasons set forth above in the claim 15 rejection.
Regarding claim 2, Li discloses the method of claim 1, wherein the performance index has at least one dimension comprising at least one of:
a dimension indicative of an impact of the audio processing algorithm on resources available in the hearing device (page 16, line 35-37: MOS scoring to achieve algorithm that consumes the least power);
a dimension indicative of an enhancement of a hearing perception of the user by the processing of the audio signal; or
a dimension indicative of an adverse effect of the processing of the audio signal for the hearing perception of the user.
Regarding claim 3, Li discloses the method of claim 2, wherein the impact of the audio processing algorithm on available resources comprises at least one of:
a power consumption of the algorithm (page 16, line 35-37: MOS scoring to achieve algorithm that consumes the least power);
a computational load of executing the algorithm (paragraph spanning pages 16-17);
a memory requirement of the algorithm; or
a communication bandwidth required to execute the algorithm in a distributed processor comprising at least two processing units communicating with each other.
Regarding claim 4, Li discloses the method of claim 2, wherein the enhancement of the hearing perception of the user comprises at least one of:
a measure of a clarity of sound encoded in the audio signal;
a measure of an understandability of a speech encoded in the audio signal;
a measure of a listening effort needed for understanding information encoded in the audio signal;
a measure of a comfort when listening to sound encoded in the audio signal;
a measure of a naturalness of sound encoded in the audio signal;
a measure of a spatial perceptibility of sound encoded in the audio signal; or
a measure of a quality of sound encoded in the audio signal
(claim 4 only further limits claim 2 under the interpretation where the dimension in claim 2 is “a dimension indicative of an enhancement of a hearing perception of the user by the processing of the audio signal”, and note that claim 2 was rejected using a different interpretation of claim 2 that the limitations of claim 4 don’t further limit, and thus under this different interpretation, Li teaches claim 4).
Regarding claim 5, Li discloses the method of claim 2, wherein the adverse effect of the processing comprises at least one of:
a level of artefacts in the processed audio signal;
a level of distortions of sound encoded in the processed audio signal; or
a level of a latency for outputting the output audio signal based on the processed audio signal
(claim 5 only further limits claim 2 under the interpretation where the dimension in claim 2 is “a dimension indicative of an adverse effect of the processing of the audio signal for the hearing perception of the user”, and note that claim 2 was rejected using a different interpretation of claim 2 that the limitations of claim 5 don’t further limit, and thus under this different interpretation, Li teaches claim 5).
Regarding claim 8, Li discloses the method of claim 1, wherein the different audio processing algorithms comprise at least two audio processing algorithms configured to provide for a same signal processing goal which are associated with a differing performance index (page 16, lines 20-37), wherein the signal processing goal comprises at least one of:
an enhancement of a speech content of a single talker in the audio signal;
an enhancement of a speech content of a plurality of talkers in the audio signal;
a reproduction of sound emitted by an acoustic object in an environment of the user encoded in the audio signal;
a reproduction of sound emitted by a plurality of acoustic objects in the environment of the user encoded in the audio signal;
a reduction and/or cancelling of noise and/or reverberations in the audio signal (page 16, lines 20-37: noise reduction algorithms);
a preservation of acoustic cues contained in the audio signal;
a suppression of noise in the audio signal;
an improvement of a signal to noise ratio (SNR) in the audio signal;
a spatial resolution of sound encoded in the audio signal depending on a direction of arrival (DOA) of the sound and/or depending on a location of at least one acoustic object emitting the sound in the environment of the user;
a directivity of an audio content in the audio signal provided by a beamforming or a preservation of an omnidirectional audio content in the audio signal;
an amplification of sound encoded in the audio signal adapted to an individual hearing loss of the user; or
an enhancement of music content in the audio signal.
Claim(s) 1-11, 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bhowmik et al. (WO 2022/081260).
Regarding claim 15, Bhowmik discloses a hearing device (¶ 0002, Fig. 9, ¶ 0057, claim 15) configured be worn at an ear of a user (¶ 0002: “ear-wearable electronic systems and devices, including hearing aids”; Fig. 1, ¶ 0026), the hearing device comprising:
an input transducer (102) configured to provide an audio signal indicative of a sound detected in an environment of the user (Fig. 1, ¶ 0026: “audio processing path 101 receives an audio signal 103”);
a processor (106, 108, 110) configured to process the audio signal by at least one audio processing algorithm to generate a processed audio signal (Fig. 1, ¶ 0026: audio processing sections 106, 108, deep neural network (DNN) 110); and
an output transducer (118) configured to output an output audio signal based on the processed audio signal so as to stimulate the user's hearing (Fig. 1, ¶ 0026: reproduction of the audio signal at a receiver 118),
characterized in that the processor is further configured to
provide different audio processing algorithms each configured to be applied on the audio signal and associated with a performance index (the value in ¶ 0043 that is weighted) indicative of a performance of the audio processing algorithm when applied on the audio signal (Fig. 5, ¶ 0038-0039: upper signal processing path 502, 504, 506, and lower processing path 512, 514, 516. The processing blocks 502, 504, 506 require fewer resources than the corresponding blocks 512, 514, 516 below (or vice versa), hence they have different performance indices.);
determine a target index (triggering threshold) relative to the performance index, the target index indicative of a target performance of said processing of the audio signal (¶0041-0043: conditions and/or events trigger change of DNN state. For example, decreasing battery power sets the target power consumption to a lower level.);
select, depending on the target index, at least one of the processing algorithms (Figs. 6, 7, ¶ 0044: select different DNN states based on signals from detector 702); and
apply the selected processing algorithm on the audio signal (Fig. 5, ¶ 0039: the selected path (either 502, 504, 506 or 512, 514, 516) is applied to audio signal 500).
Claim 1 recites similar limitations as claim 15, and is rejected for the same reasons set forth above in the claim 15 rejection.
Regarding claim 2, Bhowmik discloses the method of claim 1, wherein the performance index has at least one dimension comprising at least one of:
a dimension indicative of an impact of the audio processing algorithm on resources available in the hearing device (¶ 0039: “one of the other of these DNNS 504, 514 and latent representations 502, 512 may require fewer resources than the other”) (¶ 0069: “detecting an available battery power of the earwearable device; and based on the available battery power reaching a threshold, changing a state of the DNN which affects resource consumption by the DNN”);
a dimension indicative of an enhancement of a hearing perception of the user by the processing of the audio signal; or
a dimension indicative of an adverse effect of the processing of the audio signal for the hearing perception of the user.
Regarding claim 3, Bhowmik discloses the method of claim 2, wherein the impact of the audio processing algorithm on available resources comprises at least one of:
a power consumption of the algorithm (¶ 0069: “detecting an available battery power of the earwearable device; and based on the available battery power reaching a threshold, changing a state of the DNN which affects resource consumption by the DNN”);
a computational load of executing the algorithm;
a memory requirement of the algorithm; or
a communication bandwidth required to execute the algorithm in a distributed processor comprising at least two processing units communicating with each other.
Regarding claim 4, Bhowmik discloses the method of claim 2, wherein the enhancement of the hearing perception of the user comprises at least one of:
a measure of a clarity of sound encoded in the audio signal;
a measure of an understandability of a speech encoded in the audio signal;
a measure of a listening effort needed for understanding information encoded in the audio signal;
a measure of a comfort when listening to sound encoded in the audio signal;
a measure of a naturalness of sound encoded in the audio signal;
a measure of a spatial perceptibility of sound encoded in the audio signal; or
a measure of a quality of sound encoded in the audio signal
(claim 4 only further limits claim 2 under the interpretation where the dimension in claim 2 is “a dimension indicative of an enhancement of a hearing perception of the user by the processing of the audio signal”, and note that claim 2 was rejected using a different interpretation of claim 2 that the limitations of claim 4 don’t further limit, and thus under this different interpretation, Bhowmik teaches claim 4).
Regarding claim 5, Bhowmik discloses the method of claim 2, wherein the adverse effect of the processing comprises at least one of:
a level of artefacts in the processed audio signal;
a level of distortions of sound encoded in the processed audio signal; or
a level of a latency for outputting the output audio signal based on the processed audio signal
(claim 5 only further limits claim 2 under the interpretation where the dimension in claim 2 is “a dimension indicative of an adverse effect of the processing of the audio signal for the hearing perception of the user”, and note that claim 2 was rejected using a different interpretation of claim 2 that the limitations of claim 5 don’t further limit, and thus under this different interpretation, Bhowmik teaches claim 5).
Regarding claim 6, Bhowmik discloses the method of claim 1, wherein the determining the target index comprises at least one of:
receiving, from a user interface, a user command indicative of the target index (¶ 0043-0044: user preference setting);
evaluating the audio signal, wherein the target index is determined based on the evaluated audio signal;
receiving, from a sensor included in the hearing device, sensor data, wherein the target index is determined based on the sensor data; or
acquiring information about resources available in the hearing device, wherein the target index is determined based on the information (¶ 0043: battery level).
Regarding claim 7, Bhowmik discloses the method of claim 6, wherein the user command is indicative of a value desired by the user of the performance index
(claim 7 only further limits claim 6 under the interpretation where the determining the target index in claim 6 comprises “receiving, from a user interface, a user command indicative of the target index”, and note that claim 6 was rejected using a different interpretation of claim 6 that the limitations of claim 7 don’t further limit, and thus under this different interpretation, Bhowmik teaches claim 7).
Regarding claim 8, Bhowmik discloses the method of claim 1, wherein the different audio processing algorithms comprise at least two audio processing algorithms configured to provide for a same signal processing goal which are associated with a differing performance index (page 16, lines 20-37), wherein the signal processing goal comprises at least one of:
an enhancement of a speech content of a single talker in the audio signal (¶ 0021);
an enhancement of a speech content of a plurality of talkers in the audio signal;
a reproduction of sound emitted by an acoustic object in an environment of the user encoded in the audio signal (¶ 0021);
a reproduction of sound emitted by a plurality of acoustic objects in the environment of the user encoded in the audio signal (¶ 0021);
a reduction and/or cancelling of noise and/or reverberations in the audio signal;
a preservation of acoustic cues contained in the audio signal;
a suppression of noise in the audio signal;
an improvement of a signal to noise ratio (SNR) in the audio signal (¶ 0021);
a spatial resolution of sound encoded in the audio signal depending on a direction of arrival (DOA) of the sound and/or depending on a location of at least one acoustic object emitting the sound in the environment of the user;
a directivity of an audio content in the audio signal provided by a beamforming or a preservation of an omnidirectional audio content in the audio signal;
an amplification of sound encoded in the audio signal adapted to an individual hearing loss of the user; or
an enhancement of music content in the audio signal (¶ 0021).
Regarding claim 9, Bhowmik discloses the method of claim 1, wherein the different audio processing algorithms comprise a first set of audio processing algorithms (Fig. 5: 502, 504, and 506 can be considered a set) (alternatively: ¶ 0039: “The use of a different latent representation can be used together with other state changes of the DNN” meaning if 502, 504, and 506 are considered one algorithm, the algorithm can be differed by using different 502’s with the same 504 and 506, thus creating a first set of algorithms) and a second set of audio processing algorithms (Fig. 5: 512, 514, and 516 can be considered a set) (alternatively: ¶ 0039: “The use of a different latent representation can be used together with other state changes of the DNN” meaning if 512, 514, and 516 are considered one algorithm, the algorithm can be differed by using different 512’s with the same 514 and 516, thus creating a second set of algorithms), wherein at least one of the audio processing algorithms of the first set and at least one of the audio processing algorithms of the second set are configured to provide for a same signal processing goal (e.g., to save battery life) and are associated with a differing performance index (¶ 0043: different weight combinations).
Regarding claim 10, Bhowmik discloses the method of claim 9, wherein, depending on the target index, at least two of the audio processing algorithms of the first set or the second set are selected to be applied in a sequence and/or in parallel on the audio signal to generate the processed audio signal (Fig. 5:502, 504, and 506 are applied in sequence, as are 512, 514, and 516).
Regarding claim 11, Bhowmik discloses the method of claim 9, wherein the audio processing algorithms comprise at least one neural network (NN) (Fig. 5: DNN 1 and DNN 2).
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.
Claim(s) 12-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bhowmik in view of Aydin et al. (US 2022/0084170).
Regarding claim 12, Bhowmik discloses the method of claim 11, wherein the NN comprises an transform part (502, 512) configured to transform the audio signal, and a inverse transform part (506, 516) configured to inverse transform the transformed audio signal (Fig. 5 and ¶ 0039).
Bhowmik is not relied upon to disclose wherein the NN comprises an encoder part configured to encode the audio signal, and a decoder part configured to decode the encoded audio signal.
In a similar field of endeavor, Aydin discloses that for a neural network, an encoder part can be used as a transform part configured to encode (via transform) a signal, and that a decoder part can be used as a transform part configured to decode (via transform) the encoded (transformed) signal (¶ 0024).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the transform part as an encoder part configured to encode (via transform) the audio signal, and to configure the inverse transform part as a decoder part configured to decode (via inverse transform) the encoded (transformed) audio signal,
which would result in: wherein the NN comprises an encoder part (502, 512) configured to encode the audio signal, and a decoder part (506, 516) configured to decode the encoded audio signal,
the motivation being to perform the simple substitution of parts for transforming a signal into a latent representation for other parts, to obtain predictable results of parts that transform a signal into a latent representation. See MPEP § 2143(B).
Regarding claim 13, Bhowmik-Aydin discloses the method of claim 12, and Bhowmik discloses wherein the different audio processing algorithms comprise a first NN (502, 504, and 506) comprising the encoder (in view of Aydin) part (502) and a first decoder part (506), and a second NN (512, 514, and 516) comprising the encoder (in view of Aydin) part (512) and a second decoder (in view of Aydin) part (516) differing from the first decoder part, wherein the first NN and the second NN are associated with a differing performance index (¶ 0043: different weight combinations).
The teachings of Aydin relied upon above are combinable with Bhowmik-Aydin for the same reasons set forth above in the claim 12 rejection.
Regarding claim 14, Bhowmik-Aydin discloses the method of claim 13, and Bhowmik discloses wherein the first set of audio processing algorithms comprises the first NN, and the second set of audio processing algorithms comprises the second NN (see Fig. 5).
Conclusion
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/MARK FISCHER/Primary Examiner, Art Unit 2692
/CAROLYN R EDWARDS/Supervisory Patent Examiner, Art Unit 2692