DETAILED ACTION
This office action is in response to Applicant’s Amendment/Request for Reconsideration, received on 01/07/2025. Claims 1 and 10 have been amended. Claims 2 and 11 have been cancelled. Claims 1, 4-10, 13-18 are pending and have been considered.
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 .
Response to Arguments
Applicant’s arguments, see pgs. 6-8, filed 01/07/2026, with respect to the rejection(s) of claim(s) 1 and 10 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Faubel in view of Ray. The examiner is in agreement with Applicant that Von Bulow does not disclose the amended final “estimate…” step of the independent claims; however, as the second estimated noise is now merely defined to be “a power of a part of a band of the first estimated noise” and the first estimated noise is defined to be “based at least in part on the first sound signal”, the BRI of this claim language reads on determining a power of an input signal containing noise. The examiner respectfully asserts that Faubel teaches these limitations, see [0051]-[0052] in view of Fig. 1. See updated rejections below.
Claim Rejections - 35 USC § 103
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 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) 1, 4, 9-10, 13, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faubel et al. (US-20240203439-A1), hereinafter Faubel, in view of Ray et al. (US-20180233158-A1), hereinafter Ray.
Regarding claim 1, Faubel discloses: a sound apparatus (Abstract, hybrid noise-reducer) comprising:
a microphone configured to collect a sound and generate a first sound signal ([0063] a noisy signal is obtained from a microphone);
processing circuitry ([0040] For convenience in processing [Indicative of processing circuitry, i.e. a processor]) configured to:
estimate an estimated noise ([0051] a noise estimator 44 that receives the input remainder-spectrum 22 and provides an estimate 46 of the noise that is present within it), wherein the estimated noise includes a first estimated noise ([0049] The first noise-reduction path 24 comprises a feature-extraction circuit 32 that receives the input base-spectrum 20 and extracts feature information from the input base-spectrum 20… Based in part on this feature information, the dynamic neural network 34 outputs the first spectral-coefficients 26 [Spectral coefficient output from a noise-reduction path 24 indicates the spectral coefficients were designed to reduce noise, a base-spectrum tracks to a first noise]) and a second estimated noise ([0051] The second noise-reduction path 36 comprises a noise estimator 44 that receives the input remainder-spectrum 22 and provides an estimate 46 of the noise that is present within it [Noise determined from a remainder-spectrum tracks to a second noise]);
control a gain of the first sound signal based at least in part on the first estimated noise ([0058] A useful method is to set the foregoing gain based on a multivariate function of those first spectral-coefficients 26 that are within a window of frequencies, referred to herein as the “control window.” [First spectral coefficients represent features extracted from the first noise-reduction path (indicating the features represent noise), [0049].]) and output a second sound signal that is a gain-adjusted version of the first sound signal ([Fig. 1, Output Remainder Spectrum 42 corresponding to a signal Y(k, l), representative of a sound signal], [Applying gain to spectral coefficients (as is performed using the weighting module 52) indicates the remainder spectrum to be output from the weighting module which is a gain adjusted version of the first sound signal, i.e. that received by noise estimator 44]); and,
estimate the first estimated noise based at least in part on the first sound signal ([0046] Referring back to FIG. 1, the input base-spectrum 20 is provided to a first noise-reduction path 24. The first noise-reduction path 24 calculates first spectral-coefficients 26, W.sub.DNN(k, l), that define a filter [Output of coefficients defining a filter indicates those coefficients are calculated to filter noise]); and,
estimate a power of a part of a band of the first estimated noise as the second estimated noise irrespective of the second sound signal ([Fig. 1, Output Estimate of Noise 46 used for determining Power presence at filter calculator 48], [0051] That estimate 46, along with the input remainder-spectrum 22, is provided to a filter calculator 48, [0052] The filter calculator 48 outputs a filter comprising filter coefficients 50 that have been selected to suppress noise present in the input remainder-spectrum 22. A filter coefficient 50 corresponding to a frequency component of the input remainder-spectrum 22 takes on a value indicative of the likelihood that the power present at that frequency is speech, [The examiner asserts that determining an indication of what power corresponds to, i.e. speech/noise, requires determining the power to make that indication. Further, as the coefficient representing power is based on a frequency width k, indicating that each coefficient represents the noise of a part of a band of a first estimated noise 44, wherein that first estimated noise is based on input sound signal 18 and not the second sound signal, i.e. that later determined in component 52. The noise is estimated without considering the second sound signal as the second sound signal hasn’t been created yet]).
Faubel does not disclose:
perform filter processing to reduce a component of a predetermined frequency band of the second sound signal based at least in part on the second estimated noise.
Ray discloses:
perform filter processing to reduce a component of a predetermined frequency band of the second sound signal based at least in part on the second estimated noise ([0031] The signal path sub-system 306 modifies the primary sub-band frame signal by adaptively subtracting noise components from the primary signal c(k) to create a noise-cancelled signal c′(k) and applying the modifiers, generated in the analysis path sub-system 304, to the noise-cancelled signal c′(k) to produce an output [Applying modifiers, i.e. filtering operations, to a previously noise-cancelled signal c’(k) indicates that the modifiers are applied to the second sound signal, i.e. that which has been noise cancelled, wherein the modifiers are generated based on sub-band considerations, [0033]. Extending this operation to a “second estimated noise” does not prevent the interpretation of Ray asserted above: the signals are claimed to be band signals, with k indicating a specific sub-band ([0030]), this indicates that any additional k value beyond 1 is a second estimated noise for a second predetermined (in terms of width) frequency band of a second sound signal. Further, wherein applying modifiers (representing gain masks and/or noise gates, [0031]) to a noise-cancelled signal tracks to performing filter processing for reduction of frequency components on a second sound signal in view of the previously disclosed second sound signal of Faubel]).
Faubel and Ray are considered analogous art within noise cancellation methods. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel to incorporate the teachings of Ray, because of the novel way to handle quiet speaking or other scenarios with low signal-to-noise ratio for increased auditory understanding (Ray, [0004]).
Regarding claim 4, Faubel in view of Ray discloses: the sound processing apparatus according to claim 1.
Ray further discloses:
wherein the processing circuitry is configured to estimate a noise component in each of a plurality of frequency bands ([0030] In one example, the frequency analysis module 302 separates the acoustic signals into frequency sub-bands, [0031] In various example embodiments, the analysis path sub-system 304 processes the sub-band frame signals to identify signal features, distinguish between speech and noise components [Distinguishment of speech and noise indicates identification of noise]) and,
estimate the second estimated noise based on an estimation result of the noise component in each of the plurality of frequency bands ([0032] The noise subtraction engine 308 receives the sub-band frame signal c(k) and f(k) from the frequency analysis module 302 and, using techniques described below, the noise subtraction engine 308 cancels noise components from one or more primary sub-band signals [A sub-band frame noise subtraction analysis applied to one or more sub-band frames indicates that a second estimated noise is gathered through the individual subtraction of each noise component identified in the plurality of sub-bands. Similarly, the individual subtractions can be added to give a second estimated noise representing the combination of individual sub-bands]).
Regarding claim 9, Faubel in view of Ray discloses: the sound processing apparatus according to claim 1.
Faubel further discloses:
control the gain based on a level of the estimated noise and a level of the first sound signal ([0058] A useful method is to set the foregoing gain based on a multivariate function of those first spectral-coefficients 26 that are within a window of frequencies, where, [0048] In a preferred embodiment, a first spectral-coefficient 26 that corresponds to a frequency within the baseband takes on a value indicative of the likelihood that the power present in the input base-spectrum 20 at that frequency is speech [Controlling gain based on first-spectral coefficients, where those coefficients are corresponding to likelihood of speech, i.e. also indicative of the level of noise, where the coefficients are gathered from a first sound signal 20 of Fig. 1]); and,
perform the filter processing based at least in part on the level of the estimated noise ([0052] The filter calculator 48 outputs a filter comprising filter coefficients 50 that have been selected to suppress noise present in the input remainder-spectrum 22, where, [0066] The method 64 continues with a filtering step 76, in which the relevant filters are applied to the input base-spectrum 20 and the input remainder-spectrum 22 [Generation of filters to suppress noise to be used in a later filtering step indicates that the filtering step is based at least in part on the estimated noise represented in the filter coefficients]).
Regarding claim 10, Faubel discloses: a sound processing method (Abstract, hybrid noise-reducer) comprising:
collecting a sound and generating a first sound signal using a microphone ([0063] a noisy signal is obtained from a microphone);
estimating an estimated noise ([0051] a noise estimator 44 that receives the input remainder-spectrum 22 and provides an estimate 46 of the noise that is present within it) by performing first noise estimation processing ([0049] The first noise-reduction path 24 comprises a feature-extraction circuit 32 that receives the input base-spectrum 20 and extracts feature information from the input base-spectrum 20… Based in part on this feature information, the dynamic neural network 34 outputs the first spectral-coefficients 26 [Spectral coefficient output from a noise-reduction path 24 indicates the spectral coefficients were designed to reduce noise, a base-spectrum tracks to a first noise]) and second noise estimation processing ([0051] The second noise-reduction path 36 comprises a noise estimator 44 that receives the input remainder-spectrum 22 and provides an estimate 46 of the noise that is present within it [Noise determined from a remainder-spectrum tracks to a second noise]), wherein the first noise estimation processing comprises estimating a first estimated noise based at least in part on the first sound signal ([0046] Referring back to FIG. 1, the input base-spectrum 20 is provided to a first noise-reduction path 24. The first noise-reduction path 24 calculates first spectral-coefficients 26, W.sub.DNN(k, l), that define a filter [Output of coefficients defining a filter indicates those coefficients are calculated to filter noise]), wherein the second noise estimation processing comprises estimating a power of a part of a band of the first estimated noise as the second estimated noise irrespective of the sound signal ([Fig. 1, Output Estimate of Noise 46 used for determining Power presence at filter calculator 48], [0051] That estimate 46, along with the input remainder-spectrum 22, is provided to a filter calculator 48, [0052] The filter calculator 48 outputs a filter comprising filter coefficients 50 that have been selected to suppress noise present in the input remainder-spectrum 22. A filter coefficient 50 corresponding to a frequency component of the input remainder-spectrum 22 takes on a value indicative of the likelihood that the power present at that frequency is speech, [The examiner asserts that determining an indication of what power corresponds to, i.e. speech/noise, requires determining the power to make that indication. Further, as the coefficient representing power is based on a frequency width k, indicating that each coefficient represents the noise of a part of a band of a first estimated noise 44, wherein that first estimated noise is based on input sound signal 18 and not the second sound signal, i.e. that later determined in component 52. The noise is estimated without considering the second sound signal as the second sound signal hasn’t been created yet];
controlling a gain of the first sound signal based on the first estimated noise ([0058] A useful method is to set the foregoing gain based on a multivariate function of those first spectral-coefficients 26 that are within a window of frequencies, referred to herein as the “control window.” [First spectral coefficients represent features extracted from the first noise-reduction path (indicating the features represent noise), [0049].]) and outputting the second sound signal that is a gain-adjusted version of the first sound signal based at least in part on the first estimated noise ([Fig. 1, Output Remainder Spectrum 42 corresponding to a signal Y(k, l), representative of a sound signal], [Applying gain to spectral coefficients (as is performed using the weighting module 52) indicates the remainder spectrum to be output from the weighting module which is a gain adjusted version of the first sound signal, i.e. that received by noise estimator 44]); and,
Faubel does not disclose:
performing filter processing to reduce a component of a predetermined frequency band of the second sound signal based at least in part on the second estimated noise.
Ray discloses:
performing filter processing to reduce a component of a predetermined frequency band of the second sound signal based at least in part on the second estimated noise ([0031] The signal path sub-system 306 modifies the primary sub-band frame signal by adaptively subtracting noise components from the primary signal c(k) to create a noise-cancelled signal c′(k) and applying the modifiers, generated in the analysis path sub-system 304, to the noise-cancelled signal c′(k) to produce an output [Applying modifiers, i.e. filtering operations, to a previously noise-cancelled signal c’(k) indicates that the modifiers are applied to the second sound signal, i.e. that which has been noise cancelled, wherein the modifiers are generated based on sub-band considerations, [0033]]).
Faubel and Ray are considered analogous art within noise cancellation methods. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel to incorporate the teachings of Ray, because of the novel way to handle quiet speaking or other scenarios with low signal-to-noise ratio for increased auditory understanding (Ray, [0004]).
Regarding claim 13, Faubel in view of Ray discloses: the sound processing method according to claim 10.
Ray further discloses:
wherein the second noise estimation processing comprises estimating a noise component in each of a plurality of frequency bands ([0030] In one example, the frequency analysis module 302 separates the acoustic signals into frequency sub-bands, [0031] In various example embodiments, the analysis path sub-system 304 processes the sub-band frame signals to identify signal features, distinguish between speech and noise components [Distinguishment of speech and noise indicates identification of noise]) and,
estimating the second estimated noise based on an estimation result of the noise component in each of the plurality of frequency bands ([0032] The noise subtraction engine 308 receives the sub-band frame signal c(k) and f(k) from the frequency analysis module 302 and, using techniques described below, the noise subtraction engine 308 cancels noise components from one or more primary sub-band signals [A sub-band frame noise subtraction analysis applied to one or more sub-band frames indicates that a second estimated noise is gathered through the individual subtraction of each noise component identified in the plurality of sub-bands. Similarly, the individual subtractions can be added to give a second estimated noise representing the combination of individual sub-bands]).
Regarding claim 18, Faubel in view of Ray discloses: the sound processing method according to claim 10.
Faubel further discloses:
controlling the gain based on a level of the estimated noise and a level of the first sound signal ([0058] A useful method is to set the foregoing gain based on a multivariate function of those first spectral-coefficients 26 that are within a window of frequencies, where, [0048] In a preferred embodiment, a first spectral-coefficient 26 that corresponds to a frequency within the baseband takes on a value indicative of the likelihood that the power present in the input base-spectrum 20 at that frequency is speech [Controlling gain based on first-spectral coefficients, where those coefficients are corresponding to likelihood of speech, i.e. also indicative of the level of noise, where the coefficients are gathered from a first sound signal 20 of Fig. 1]); and,
performing the filter processing based on the level of the estimated noise ([0052] The filter calculator 48 outputs a filter comprising filter coefficients 50 that have been selected to suppress noise present in the input remainder-spectrum 22, where, [0066] The method 64 continues with a filtering step 76, in which the relevant filters are applied to the input base-spectrum 20 and the input remainder-spectrum 22 [Generation of filters to suppress noise to be used in a later filtering step indicates that the filtering step is based at least in part on the estimated noise represented in the filter coefficients]).
Claim(s) 5, 6, 14, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faubel in view of Ray, further in view of Ramprashad (US-10636434-B1).
Regarding claim 5, Faubel in view of Ray discloses: the sound processing apparatus according to claim 4.
Faubel in view of Ray does not disclose:
wherein the processing circuitry is configured to perform the filter processing in a band narrower than the plurality of frequency bands.
Ramprashad discloses:
wherein the processing circuitry is configured to perform the filter processing in a band narrower than the plurality of frequency bands ([Fig. 4], [Col. 20, Lines 15-20] According to an aspect of this disclosure, a system can determine that frequency band 405 does not need any more suppression and thus masker components in this band can be used as part of the subset that can be leveraged for additional echo and/or noise suppression for at least adjacent frequency bands (such as frequency bands 403 and 407) [Indication of additional noise suppression in some of the plurality of bands indicates filtering in a band narrower than the plurality]).
Faubel, Ray, and Ramprashad are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Ramprashad, because of the novel way to simultaneously (Ramprashad, [Col. 1, Lines 40-60, Col. 2, Lines 1-15]).
Regarding claim 6, Faubel in view of Ray discloses: the sound processing apparatus according to claim 1.
Faubel in view of Ray does not disclose:
wherein the processing circuitry is configured to increase an amount of reduction in the filter processing as a level of the estimated noise is increased.
Ramprashad discloses:
wherein the processing circuitry is configured to increase an amount of reduction in the filter processing as a level of the estimated noise is increased ([Fig. 3], [Col. 20, Lines 20-25] Frequency band 405 can be in the “Set No Suppress” bins for which no suppression is applied and frequency bands 403 and 407 can be in the “Set Suppress” bins for which some suppression is applied [It can be seen in Fig. 3 that the reasons bands 403 and 407 are selected for suppression is because of their respective levels of noise compared to speech]).
Faubel, Ray, and Ramprashad are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Ramprashad, because of the novel way to simultaneously exploit microphones for noise and echo control resulting in a maximized signal-to-noise ratio for increased intelligibility (Ramprashad, [Col. 1, Lines 40-60, Col. 2, Lines 1-15]).
Regarding claim 14, Faubel in view of Ray discloses: the sound processing method according to claim 13.
Faubel in view of Ray does not disclose:
performing the filter processing in a band narrower than the plurality of frequency bands.
Ramprashad discloses:
performing the filter processing in a band narrower than the plurality of frequency bands ([Fig. 4], [Col. 20, Lines 15-20] According to an aspect of this disclosure, a system can determine that frequency band 405 does not need any more suppression and thus masker components in this band can be used as part of the subset that can be leveraged for additional echo and/or noise suppression for at least adjacent frequency bands (such as frequency bands 403 and 407) [Indication of additional noise suppression in some of the plurality of bands indicates filtering in a band narrower than the plurality]).
Faubel, Ray, and Ramprashad are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Ramprashad, because of the novel way to simultaneously exploit microphones for noise and echo control resulting in a maximized signal-to-noise ratio for increased intelligibility (Ramprashad, [Col. 1, Lines 40-60, Col. 2, Lines 1-15]).
Regarding claim 15, Faubel in view of Ray discloses: the sound processing method according to claim 10.
Faubel in view of Ray does not disclose:
increasing an amount of reduction in the filter processing as a level of the estimated noise is increased.
Ramprashad discloses:
increasing an amount of reduction in the filter processing as a level of the estimated noise is increased ([Fig. 3], [Col. 20, Lines 20-25] Frequency band 405 can be in the “Set No Suppress” bins for which no suppression is applied and frequency bands 403 and 407 can be in the “Set Suppress” bins for which some suppression is applied [It can be seen in Fig. 3 that the reasons bands 403 and 407 are selected for suppression is because of their respective levels of noise compared to speech]).
Faubel, Ray, and Ramprashad are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Ramprashad, because of the novel way to simultaneously exploit microphones for noise and echo control resulting in a maximized signal-to-noise ratio for increased intelligibility (Ramprashad, [Col. 1, Lines 40-60, Col. 2, Lines 1-15]).
Claim(s) 7, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faubel in view of Ray, further in view of Von Bulow et al. (US-20180047410-A1), hereinafter Von Bulow.
Regarding claim 7, Faubel in view of Ray discloses: the sound processing apparatus according to claim 1.
Faubel in view of Ray does not disclose:
wherein an amount of reduction in the filter processing has a maximum and a minimum
Von Bulow further discloses:
wherein an amount of reduction in the filter processing has a maximum and a minimum ([0138] Based on the noise estimate, a max gain component 808 computes a gain coefficient for the gain stage 201, and [0065] The reference gain may be computed from the noise estimate by searching for a minimum attenuation, this value is applied as a reference gain to the full bandwidth [Applying gain to a signal tracks to a type of filter processing]).
Faubel, Ray, and Von Bulow are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Von Bulow, because of the novel way to set an appropriate attenuation level of signals based on the signal-to-noise ratio relative to the frequency band to better distinguish side tones from far-end signals (Von Bulow, [0018]).
Regarding claim 16, Faubel in view of Ray discloses: the sound processing method according to claim 10.
Faubel in view of Ray does not disclose:
wherein an amount of reduction in the filter processing has a maximum and a minimum.
Von Bulow further discloses:
wherein an amount of reduction in the filter processing has a maximum and a minimum ([0138] Based on the noise estimate, a max gain component 808 computes a gain coefficient for the gain stage 201, and [0065] The reference gain may be computed from the noise estimate by searching for a minimum attenuation, this value is applied as a reference gain to the full bandwidth [Applying gain to a signal tracks to a type of filter processing]).
Faubel, Ray, and Von Bulow are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Von Bulow, because of the novel way to set an appropriate attenuation level of signals based on the signal-to-noise ratio relative to the frequency band to better distinguish side tones from far-end signals (Von Bulow, [0018]).
Claim(s) 8, 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Faubel in view of Ray, further in view of Han (US-20120127341-A1).
Regarding claim 8, Faubel in view of Ray discloses: the sound processing apparatus according to claim 1.
Faubel in view of Ray does not disclose:
wherein the processing circuitry is configured to obtain image data, and estimate the estimated noise based on the image data.
Han discloses:
wherein the processing circuitry is configured to obtain image data, and estimate the estimated noise based on the image data ([Fig. 2, “Image Input Unit 210”], [0055] In this case, the noise removing mode may be implemented as a mode in which all noises are automatically removed through detection of whether the noise exists in the captured image).
Faubel, Ray, and Han are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray to incorporate the teachings of Han, because of the novel way to remove audio noise present in an environment to be detected by an image input device for increased audio intelligibility in environments with large background noises (Han, [0006]).
Regarding claim 17, Faubel in view of Ray discloses: the sound processing method according to claim 10.
Faubel in view of Ray does not disclose:
obtaining image data, wherein the noise is estimated based on image data.
Han discloses:
obtaining image data, wherein the noise is estimated based on image data ([Fig. 2, “Image Input Unit 210”], [0055] In this case, the noise removing mode may be implemented as a mode in which all noises are automatically removed through detection of whether the noise exists in the captured image).
Faubel, Ray, and Han are considered analogous art within adaptive noise cancellation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Faubel in view of Ray, to incorporate the teachings of Han, because of the novel way to remove audio noise present in an environment to be detected by an image input device for increased audio intelligibility in environments with large background noises (Han, [0006]).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Shanmugam et al. (US-20200312342-A1) discloses “An audio processing system has multiple microphones that capture an audio signal. A noise suppression circuit analyses the audio signal to detect a type of noise present in the signal (e.g., stationary or non-stationary background noise). Based on the detected background noise type, the system operates in either a first or second mode of operation. In the first mode (stationary noise detected), one microphone is used to enhance a speech signal from the audio signal, and in the second mode (non-stationary noise detected), more than one microphone is used to enhance the speech signal. Processing more than one microphone input signal requires additional complexity and more processing power than one-microphone speech enhancement, so by classifying the background noise type and then switching between one microphone or N-microphones based speech enhancement, processing power is reduced during stationary noise conditions” (abstract). See entire document.
Makino (US-20130191118-A1) discloses “Provided is a noise suppressing device including a framing unit that frames an input signal, a band division unit that obtains a band division signal, a band power computation unit that obtains a band power from each band division signal, a noise determination unit that determines whether each band is stationary noise or non-stationary noise, a noise band power estimation unit that estimates a band power of noise of each band, a noise suppression gain decision unit that decides a noise suppression gain of each band, a noise suppression unit that obtains a band division signal whose noise is suppressed, a band synthesis unit that obtains a framed signal whose noise is suppressed, and a frame synthesis unit that obtains an output signal whose noise is suppressed” (abstract). See entire document.
Winn (US-6108610-A) discloses “n improved adaptive spectral estimator for estimating the spectral components in a signal containing both an information signal, such as speech, and noise. A method and system provide for generating noise estimates and then only updating the noise estimates during pauses in an information signal, when speech or other information is not detected, rather than continuously updating the noise estimates. A noise estimate is calculated for each frequency band and provides for the inclusion of a variable mathematical factor that can be set by the user to produce the best sound quality” (abstract). See entire document.
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/THEODORE WITHEY/Examiner, Art Unit 2655
/ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655