DETAILED ACTION
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 statements (IDS) submitted on 02/07/2025 and 06/12/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Drawings
The drawings were submitted on 01/30/2024. These drawings are reviewed and accepted by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) do not fall within at least one of the four categories of patent eligible subject matter because a machine-readable medium directed to transitory-type media is non-statutory.
Regarding claim 15, it recites “a machine-readable medium”. The specification recites, “In some examples, machine readable media may include non-transitory machine readable media.” (par. 0068) Since the specification does not explicitly define “machine-readable medium” in such a way as to exclude signals or transitory-type media, the presumption that signal embodiments are included in the scope of the claim stands. It is noted that a machine-readable medium referring to a signal, carrier wave, or transmission medium, does not fall within any one of the statutory categories under 35 USC 101, so that it is not eligible for a patent (See “Interim Examination Instructions For Evaluating Subject Matter Eligibility Under 35 USC 101”, effective on August 24, 2009). Therefore, the claim as a whole is directed to non-statutory subject matter.
Claims 16-20 depend on claim 15 and are rejected under the same rationale.
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) 1, 4, 6, 8, 11, 13, 15, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et al. (US 20240098607 A1) in view of Sandell (IDS: EP 2,424,198 A2).
Regarding claims 1, 8, and 15, Srinivasan teaches:
“A method performed by a data processing system for preventing loss of audio in a communication session due to a wireless peripheral device handover” (par. 0024; ‘Accordingly, methods and systems for audio processing handover between audio devices are herein presented.’), the method comprising:
during the communication session and using a hardware processor:
“identifying a first speech feature captured by a first microphone currently used in the communication session by analyzing speech signals captured by the first microphone, the first speech feature being linguistic or acoustic features of speech of a first user, the first microphone belonging to a first peripheral device wirelessly connected to a computing device used by the first user to participate in the communication session, the linguistic features related to information contained in the speech and the acoustic features related to properties of a sound wave produced by the speech” (par. 0026; ‘In some aspects, the first audio device 100A may be part of a first wireless earbud 112A and the second audio device 100B may be part of a second wireless earbud 112B.’; par. 0028; ‘As shown in FIG. 2, the method 200 includes, at block 202, selecting the first audio device to be the primary audio input device based on a comparison of a quality of a first audio signal from a microphone of the first audio device (AQ1) and a quality of a second audio signal from a microphone of the second audio device (AQ2).’ The quality of the microphones reads on acoustic features.; par. 0077; voice quality.);
“detecting an indication of a handover condition indicating a handover from using the first microphone in the communication session to using a second microphone in the communication session, the second microphone belonging to a second peripheral device wirelessly connected to the computing device” (par. 0037; ‘FIG. 3A and FIG. 3B are signaling and event diagrams illustrating portions of a process 300 for audio processing handover between audio devices according to aspects of the disclosure.’ ‘The audio device having the higher noise level will be the secondary audio input device and will not perform any voice processing algorithms, and, in some aspects, will power down its microphone, reduce its processor load, take other actions to reduce its power consumption, or a combination thereof.’); and
“in response to the detected indication of the handover condition: identifying a second speech feature output from the second microphone by analyzing speech signals captured by the second microphone, the second speech feature output including linguistic or acoustic features” (par. 0039; ‘As shown in FIG. 3A, at block 308, the left audio device 304 sends to the decision process 302 a first indication of the noise level on the audio from left audio device 304 (N.sub.L1), and at block 320, the right audio device 306 sends to the decision process 302 a first indication of the noise level on the audio from the right audio device 306 (N.sub.R1).’);
“comparing the first speech feature with the second speech feature to produce a comparison result” (par. 0039; ‘At block 312, the decision process 302 determines that the noise level on the left audio device 304 is greater than the noise level on the right audio device 306 (e.g., N.sub.L1>N.sub.R1).’); and
“[[determining, based upon the comparison result, that the first user is not using the second microphone]], and in response, causing the handover to be blocked or reversed by continuing to utilize the first microphone for the communication session, and not using the second microphone in the communication session” (par. 0041; ‘In the example illustrated in FIG. 3A, this condition triggers a potential handover, so at block 332, the decision process 302 activates the left audio device 304.’ ‘In this example, at block 338, the decision process 302 determines the noise level on the left audio device 304 is the same as the noise level on the right audio device 306 (e.g., N.sub.L2=N.sub.R3), and so there is no benefit to having the left audio device 304 take over the primary role from the right audio device 306. Thus, at block 340, the decision process 302 instructs the left audio device 304 to deactivate, and at block 342, the left audio device 304 does deactivate.’).
However, Srinivasan does not expressly teach “determining, based upon the comparison result, that the first user is not using the second microphone” in “determining, based upon the comparison result, that the first user is not using the second microphone, and in response, causing the handover to be blocked or reversed by continuing to utilize the first microphone for the communication session, and not using the second microphone in the communication session.”
Sandell teaches:
“determining, based upon the comparison result, that the first user is not using the second microphone, and in response, causing the handover to be blocked or reversed by continuing to utilize the first microphone for the communication session, and not using the second microphone in the communication session” (par. 0044; ‘If the controller 12 does not detect audible sound within that time limit, the controller 12 would send the incoming audio signals to the default speaker.’).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Srinivasan’s handover methods by incorporating Sandell’s method of polling microphones in order to determine, based upon the comparison result, that a user is not using a second microphone, thus not go through with a handover. The combination allows for dynamically routing incoming audio signals to desired speakers. (Sandell: par. 0003)
Regarding claims 4 (dep. on claim 1), 11 (dep. on claim 8), and 18 (dep. on claim 15), the combination of Srinivasan in view of Sandell further teaches:
“wherein detecting the handover condition indicating the handover of the first microphone to the second microphone comprises a notification that the handover already occurred” (Srinivasan: par. 0076; ‘The HDMA receives inputs from both primary and secondary earbuds and when necessary recommends a handover with the following information: the reason for the handover, handover urgency (critical, high, or low), and a timestamp.’ Timestamp of handovers reads on handover already occurred.).
Regarding claims 6 (dep. on claim 1), 13 (dep. on claim 8), and 20 (dep. on claim 15) the combination of Srinivasan in view of Sandell further teaches:
“wherein detecting the handover condition indicating a handover of the first microphone to a second microphone comprises a soft handover where both the first microphone and the second microphone are both sending audio to the communication session and wherein blocking the handover or reversing the handover comprises terminating a link to the second microphone” (Srinivasan: par. 0041; ‘Thus, at block 340, the decision process 302 instructs the left audio device 304 to deactivate, and at block 342, the left audio device 304 does deactivate. The example continues in FIG. 3B.’).
Claim(s) 2, 3, 5, 9, 10, 12, 16, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan in view of Sandell as applied to claim 1 above, and further in view of Oh (US 20230102049 A1).
Regarding claims 2 (dep. on claim 1), 9 (dep. on claim 8), and 16 (dep. on claim 15), the combination of Srinivasan in view of Sandell teaches voice features (voice quality).
However, Srinivasan in view of Sandell does not expressly teach:
“wherein the first speech feature is a linguistic feature comprising a first transcription of words uttered by the first user and wherein the second speech feature is a linguistic feature comprising a second transcription of output from the second microphone and wherein comparing the first speech feature with the second speech feature comprises comparing the first and second transcriptions using a generative artificial intelligence model to determine if the second transcription is a continuation of a conversation of the first transcription.”
Oh teaches:
“wherein the first speech feature is a linguistic feature comprising a first transcription of words uttered by the first user and wherein the second speech feature is a linguistic feature comprising a second transcription of output from the second microphone and wherein comparing the first speech feature with the second speech feature comprises comparing the first and second transcriptions using a generative artificial intelligence model to determine if the second transcription is a continuation of a conversation of the first transcription” (par. 0044; ‘by using an automatic voice recognition (ASR) module that converts the user's voice input into text data…’; par. 0084; ‘Alternatively, the processor 130 may identify the type of ambient noise using an AI model.’; par. 0127; ‘After performing voice recognition on the user voice input and obtaining information corresponding to the voice recognition result, if the voice of another user is not detected, the processor 130 may output information corresponding to the obtained voice recognition result.’).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the voice quality measuring methods of Srinivasan in view of Sandell by incorporating the ASR module and AI model taught by Oh in order to compare transcriptions using the AI model to determine continuation of a conversation. The combination provides a way of outputting response information based on a type of ambient noise. (Oh: par. 0005)
Regarding claims 3 (dep. on claim 1), 10 (dep. on claim 8), and 17 (dep. on claim 15), the combination of Srinivasan in view of Sandell and Oh further teaches:
“wherein the first and second speech features are acoustic features that comprise one or more of a tone, pitch, speaking rate, frequency, voice onset time, spectral distribution, or dynamic range and wherein comparing the first speech feature with the second speech feature comprises determining a difference between the first and second speech features and wherein determining, based upon the comparison result, that the voice of the first user is not present in the second microphone comprises determining that the difference between the first and second speech features exceeds a threshold difference” (Oh: par. 0015; ‘The method may include detecting the ambient noise; and distinguishing the voice input of the user and the ambient noise using a frequency analysis.’; par. 0083; ‘For example, the processor 130 may perform frequency analysis by extracting features such as amplitude and period of the ambient noise signal, and identify whether the ambient noise corresponds to a voice of another user, whether the ambient noise corresponds to a sound generated by another electronic apparatus, or whether the ambient noise corresponds to a sound generated in a situation that requires an immediate action of the user, such as a baby's cry or the sound of a window breaking.’; Srinivasan: par. 0080; VAD).
Regarding claims 5 (dep. on claim 1), 12 (dep. on claim 8), and 19 (dep. on claim 15), the combination of Srinivasan in view of Sandell and Oh further teaches:
“identifying linguistic features of a second user in the communication session from after the handover; and wherein determining, based upon the comparison result, that the voice of the first user is not present in the second microphone, comprises determining that the voice of the first user is not present in the second microphone based upon the comparison result and based upon identifying that the linguistic features of the second user indicate an inability to hear the first user” (Srinivasan: par. 0080; VAD; Oh: par. 0083; ‘For example, the processor 130 may perform frequency analysis by extracting features such as amplitude and period of the ambient noise signal, and identify whether the ambient noise corresponds to a voice of another user, whether the ambient noise corresponds to a sound generated by another electronic apparatus, or whether the ambient noise corresponds to a sound generated in a situation that requires an immediate action of the user, such as a baby's cry or the sound of a window breaking.’).
Claim(s) 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan in view of Sandell as applied to claim 1 above, and further in view of Zhang et al. (US 20210256979 A1).
Regarding claims 7 (dep. on claim 1) and 14 (dep. on claim 8), the combination of Srinivasan in view of Sandell does not expressly teach:
“producing, from the first speech feature, a first speech profile of the first user and producing, from the second speech feature, a second speech profile”;
“wherein comparing the first speech feature with the second speech feature to produce a comparison result comprises comparing the first speech profile and the second speech profile”; and
“wherein determining, based upon the comparison result, that the first user is not using the second microphone comprises determining that the first speech profile does not match the second speech profile.”
Zhang teaches:
“producing, from the first speech feature, a first speech profile of the first user and producing, from the second speech feature, a second speech profile” (par. 0025; ‘determining, by the wearable device, whether the first voice component matches a first voiceprint model of an authorized user, where the first voiceprint model is used to reflect an audio feature that is of the authorized user and that is collected by the first voice sensor; and determining, by the wearable device, whether the second voice component matches a second voiceprint model of the authorized user, where the second voiceprint model is used to reflect an audio feature that is of the authorized user and that is collected by the second voice sensor;’);
“wherein comparing the first speech feature with the second speech feature to produce a comparison result comprises comparing the first speech profile and the second speech profile” (par. 0025; ‘if the first voice component matches the first voiceprint model of the authorized user, and the second voice component matches the second voiceprint model of the authorized user, determining, by the wearable device, that a voicing user is an authorized user, or otherwise, determining, by the wearable device, that the voicing user is an unauthorized user.’);
“wherein determining, based upon the comparison result, that the first user is not using the second microphone comprises determining that the first speech profile does not match the second speech profile” (par. 0025; ‘if the first voice component matches the first voiceprint model of the authorized user, and the second voice component matches the second voiceprint model of the authorized user, determining, by the wearable device, that a voicing user is an authorized user, or otherwise, determining, by the wearable device, that the voicing user is an unauthorized user.’; par: 0045; ‘the recognition unit is specifically configured to perform voiceprint recognition on the first voice component and the second voice component when the first VAD value and the second VAD value each meet a preset condition.’).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Srinivasan in view of Sandell voice processing methods by incorporating Zhang’s voiceprint modeling (i.e., speech profiling) and VAD in order to determine whether a second microphone is not being used. The combination improves accuracy and security of voiceprint recognition when a user uses a voice control terminal. (Zhang: par. 0004)
Conclusion
Other pertinent prior art are cited in the PTO-892 for the applicant's consideration.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK VILLENA whose telephone number is (571)270-3191. The examiner can normally be reached 10 am - 6pm EST Monday through Friday.
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MARK . VILLENA
Examiner
Art Unit 2658
/MARK VILLENA/Examiner, Art Unit 2658