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 .
1. This communication in response to application filed 06/04/2024.
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted 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 § 103
3. 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHWIOKO et al. (Pub.No.: 2019/0228757 A1) in view of Gurijala et al. (US PAT # 10,236,006 B1).
Regarding claims 1 and 11, CHWIOKO teaches a sound masking apparatus and method, comprising:
a microphone in a vehicle (reads on vehicle 100 comprises a control means 200 which may be in the form of a controller 200. The control means 200 may be communicably coupled to the first microphone 130, see [0057]); and
a processor connected to the microphone (see [0059]),
wherein the processor is configured to
detect conversation noise using the microphone (reads on the controller comprising input means for receiving a speech intelligibility signal indicative of a speech intelligibility in a first zone of an interior of a vehicle, see [0022]),
generate a masking sound source (see [0007] and [0056]), and
mask the conversation noise by playing the masking sound source (see [0056]).
CHWIOKO features are already addressed in the rejection of independent claims 1 and 11. Although CHWIOKO teaches generating masking sound (see [0056] and [0067]), however it does not specifically teach “modulate the conversation noise”.
Yet Gurijala teaches modulating speech, signal transformation and frame manipulation (see col. 1, lines 18-20) including reverse the effect of time stretching and shrinking (see col. 23, lines 1-14) reordering/recombining audio segments (see abstract of Gurijala), spectral analysis (col. 38 and lines 30-51 and FIG.11, the PPE 1100 makes these pitch adjustments in block 1104. The PPE converts a frame to frequency components (e.g., through a Fourier transform (FFT), subband filtering or like frequency transform) (1204), see Fig. 11 and corresponding text), Mel-frequency cepstral coefficient (MFCC) from the detected sound (see Gurijala, col. 54, lines 22-67) and classifying the ambient sounds, including background conversations (see col. 2, lines 4-27).
Thus, it would have been obvious to one of an ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known audio modulation and transformation techniques, as taught by Gurijala, into CHWIOKO’s conversation masking system in order to improve the masking sound generation by rendering the captured conversation noise unintelligible through modulation before playback.
Regarding claims 2 and 12, The combination of CHWIOKO and Gurijala teaches sound masking apparatus of claim 1, wherein the processor is configured to:
determine whether a sound pressure level of a sound detected by the microphone (reads on receiving a speech intelligibility signal indicative of a speech intelligibility in a first zone of an interior of a vehicle, see CHWIOKO [0022]) is greater than a predetermined reference level and continues for a predetermined reference time or more (see Gurijala, col. 38, lines 30-45);
determine that noise is generated, when it is determined that the sound pressure level of the detected sound is greater than the predetermined reference level and continues for the predetermined reference time or more (Gurijala teaches perceptual model for a particular type of watermark, measurement of sound strength at different frequencies can be used in conjunction with equal loudness graphs to adjust the strength of the watermark signal relative to the host sound strength. This provides another aspect of spectral shaping of the watermark signal strength. Duration of a particular sound can also be used in the temporal shaping of the watermark signal strength to form a masking envelope around the sound where the watermark signal can be increased, yet still masked, see col. 19, lines 32-40 and lines 58-67);
extract a frequency characteristic from the detected sound (see Gurijala, col. 54, lines 22-67 and col. 38 and lines 30-51); and
determine whether noise generated based on the extracted frequency characteristic is conversational noise (see Gurijala, col. 13, lines 20-26).
Regarding claims 3 and 13, The combination of CHWIOKO and Gurijala teaches of claim 2, wherein the processor is configured to:
extract a Mel-frequency cepstral coefficient (MFCC) from the detected sound (see Gurijala, col. 54, lines 22-67) by a short-time fast Fourier transform (FFT) analysis (see Gurijala, col. 38 and lines 30-51. Also In FIG. 11, the PPE 1100 makes these pitch adjustments in block 1104. The PPE converts a frame to frequency components (e.g., through a Fourier transform (FFT), subband filtering or like frequency transform) (1204), see Fig. 11 and corresponding text); and
convert the extracted MFCC into a noise spectrum (see Gurijala, col. 54, lines 22-67).
Regarding claims 4 and 14, The combination of CHWIOKO and Gurijala teaches wherein the processor is configured to modulate the conversation noise in a reverse playback scheme to generate the masking sound source (Gurijala teaches reverse embedding approach provides greater robustness against pitch invariant time scaling (PITS). This approach generally provides better robustness since typically the host signal is the largest source of noise. Pitch invariant time scaling is performed by keeping the frequency axis unchanged while scaling the time axis. For example, in a spectrogram view of the audio signal (e.g., where time is along the horizontal axis and frequency is along the vertical axis), pitch invariant time scaling is obtained by resampling across just the time axis, see col. 23, lines 1-14.).
Claims 5 and 15 recite “wherein the processor is configured to modulate the conversation noise in a reordering scheme to generate the masking sound source”. CHWIOKO teaches detecting conversation noise and generating masking audio in a vehicle as discussed in [0007], [0022] and [0056], however it does not teach “reordering scheme” as recited in claims 5 and 15.
Gurijala teaches manipulating audio signals by reordering and transforming audio frames, including time-stretching, time shrinking, reversing temporal effects and recombining frames to produce modified audio signals (see abstract of Gurijala), which is considered equivalent to the claimed “reordering scheme”.
Thus, it would have been obvious to one of an ordinary skill in the art before the effective filing date of the claimed invention to utilize the known audio frame reordering technique, as taught by Gurijala, into the masking system of CHWIOKO to reduce intelligibility of conversation noise by scrambling temporal coherence
Regarding claims 6 and 16, The combination of CHWIOKO and Gurijala teaches wherein the processor is configured to:
modulate the conversation noise in a reverse playback scheme (reads on transforming audio frames, including time-stretching, time shrinking, reversing temporal effects and recombining frames to produce modified audio signals (see abstract of Gurijala));
modulate the conversation noise in a reordering scheme (reads on reversing temporal effects, see Gurijala, col. 31, line 48 through col. 32, line 3); and
overlap the conversation noise modulated in the reverse playback scheme with the conversation noise modulated in the reordering scheme to generate the masking sound source (see col. 40, lines 37-45).
Regarding claims 7 and 17, The combination of CHWIOKO and Gurijala teaches wherein the processor is configured to adjust a volume of the masking sound source with regard to a level of the conversation noise (see CHWIOKO [0074]).
Regarding claims 8 and 18, The combination of CHWIOKO and Gurijala teaches wherein the processor is configured to:
capture an image of a passenger using a camera (see CHWIOKO [0056] and [0077]); and
determine a position where the conversation noise is generated (see CHWIOKO [0056] and [0077]), based on at least one of a mouth shape of the passenger in the captured image (note that in paragraph [0056], CHWIOKO teaches the one or more cameras are arranged to provide image data corresponding to an image of one or more occupants from whom the system is arranged to mask speech within the vehicle, so recognizing the mouth shape of the passenger is considered obvious and predictable extension within the teaching of CHWIOKO), whether the passenger uses a portable terminal, or any combination thereof.
Regarding claims 9 and 19, The combination of CHWIOKO and Gurijala wherein the processor is configured to:
detect a sound using a microphone for each seat (see CHWIOKO [0022], [0033], [0034]); and
determine a position where the conversation noise is generated, based on a level of the sound detected by the microphone for each seat (reads on comparing signal from different zones, see CHWIOKO [0022], [0033], [0034]).
Regarding claims 10 and 20, The combination of CHWIOKO and Gurijala teaches wherein the processor is configured to determine at least one speaker to output the masking sound source among a plurality of speakers mounted in the vehicle based on a position where the conversation noise is generated (see CHWIOKO [0054] and [0060]).
Conclusion
4. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rasha S. AL-Aubaidi whose telephone number is (571) 272-7481. The examiner can normally be reached on Monday-Friday from 8:30 am to 5:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Ahmad Matar, can be reached on (571) 272-7488.
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/RASHA S AL AUBAIDI/Primary Examiner, Art Unit 2693