DETAILED ACTION
1. This communication is in response to the Application filed on 7/19/2024. Claims 1-15 are pending and have been examined.
Allowable Subject Matter
2. Claims 4-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim Rejections - 35 USC § 103
3. Claims 1-2, 12 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan (IEEE 2011; hereinafter Srinivasan) in view of Trompf (US 5583968; hereinafter TROMPF).
As per claim 1, Srinivasan (Title: USING A REMOTE WIRELESS MICROPHONE FOR SPEECH ENHANCEMENT IN NON-STATIONARY NOISE) discloses “A display device, comprising: a speaker; a wireless communication interface configured to communicate with a peripheral device; a microphone configured to record surrounding sounds; and a controller configured to perform [ user voice recognition ] on data recorded by the microphone, wherein the controller is configured to compensate the user voice recognition using audio data received from the peripheral device (Srinivasan, Title; Fig. 1, [Introduction, para 2-3], use of a remote wireless microphone (RWM) <read on ‘a peripheral device’> placed close to a noise source, which transmits relevant information to the primary device <read on the ‘display device’> , where it is used for noise reduction … The RWM is in this case placed near the TV, and transmits its signal to the computer <read on ‘display device .. speaker’>, where it is combined with the local microphone signal to perform noise reduction <read on to ‘compensate the user voice recognition using audio data received from the peripheral device’>).”
Srinivasan does not explicitly disclose “user voice recognition ..” However, the feature is taught by TROMPF (Title: Noise reduction for speech recognition).
In the same field of endeavor, TROMPF teaches: [Abstract] “A neural network for noise reduction for speech recognition in a noisy environment.”
Therefore, it would have been obvious to one of ordinary skill in the art at the time before the effective filing date of the claimed invention to incorporate the teachings of TROMPF in a system (as taught by Srinivasan) to provide neural network based speech recognition for noise-suppressed speech signal for any downstream application.
As per claim 2 (dependent on claim 1), Srinivasan in view of TROMPF further discloses “wherein the audio data includes at least one of recording data recorded by the peripheral device and sound source data being played by the peripheral device (Srinivasan, [Introduction, para 2-3], use of a remote wireless microphone (RWM) <read on ‘the peripheral device’ and the ‘recording data’> placed close to a noise source, which transmits relevant information to the primary device, where it is used for noise reduction).”
As per claim 12 (dependent on claim 1), Srinivasan in view of TROMPF further discloses “wherein the peripheral device comprises at least one of a remote control device, a mobile terminal, and a Bluetooth speaker that transmits a control signal to the display device (Srinivasan, [Introduction, para 2-3], a remote wireless microphone (RWM) .. which transmits relevant information to the primary device <where RWM reads on a key component of many diverse devices including a remote control device, a mobile terminal, …).”
4. Claims 3, 14 are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan in view of TROMPF, and further in view of Heo (US 20170154625; hereinafter HEO).
As per claim 3 (dependent on claim 1), Srinivasan in view of TROMPF further discloses “if the display device is not linked with the peripheral device, recognize a user voice from the data recorded by the microphone using first preprocessing data, if the display device is linked with the peripheral device, obtain second preprocessing data based on audio data received from the peripheral device, and recognize the user voice from the data recorded by the microphone using the second preprocessing data (Srinivasan, Fig. 1).”
Srinivasan in view of TROMPF does not explicitly disclose the limitations of Claim 3. However, the feature is taught by HEO (Title: Video display device and operation method therefor).
In the same field of endeavor, HEO teaches: [Abstract] “receiving at least one voice signal for a user voice acquired by at least one peripheral device .. and a voice signal for the user voice acquired by the video display device; comparing the plurality of acquired voice signals with each other; determining a voice signal subjected to voice recognition based on the comparison result; recognizing the user voice based on the determined voice signal ..” and [0176] “The control unit of the video display device may compare qualities of the plurality of acquired voice signals based on at least one of a user voice range level and a noise level of each of the plurality of acquired voice signals <read on linked or not linked, which is subject to BRI>”
Therefore, it would have been obvious to one of ordinary skill in the art at the time before the effective filing date of the claimed invention to incorporate the teachings of HEO in a system (as taught by Srinivasan and TROMPF) to determine which of the acquired voice signals to be used for voice recognition based on the acquired voice quality (voice and noise levels) which read on linked or not linked condition.
As per claim 14 (dependent on claim 1), Srinivasan in view of TROMPF further discloses “wherein the controller is configured to extract user commands from each of the data recorded by the microphone and the data recorded by the peripheral device, and [ recognize user commands that match at least two of the extracted user commands as the user's voice ] (Srinivasan, Fig. 1, [Introduction, para 2-3], a remote wireless microphone .. the local microphone <read on to receive user voice commands>).”
Srinivasan in view of TROMPF does not explicitly disclose “recognize user commands that match at least two of the extracted user commands as the user's voice ..” However, the feature is taught by HEO (Title: Video display device and operation method therefor).
In the same field of endeavor, HEO teaches: [0212] “the control unit may search for the voice signal matching the acquired voice signal from at least one of the database stored in the storage unit and the database of the network server connected through the network interface unit, and may acquire the control operation corresponding to the found voice signal” and [Abstract] “determining a voice signal subjected to voice recognition ..”
Therefore, it would have been obvious to one of ordinary skill in the art at the time before the effective filing date of the claimed invention to incorporate the teachings of HEO in a system (as taught by Srinivasan and TROMPF) to search different (extracted) voice databases for the matching of the user command to determine the user's voice to ensure more accurate voice command recognition for target application.
5. Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan in view of TROMPF, and further in view of Ganeshkumar (US 20180270565; hereinafter Ganeshkumar).
As per claim 13 (dependent on claim 1), Srinivasan in view of TROMPF further discloses “extract user commands from each of the data recorded by the microphone and the data recorded by the peripheral device, and recognize [ a command with the largest size ] among the extracted user commands as the user voice (HEO, [Abstract], receiving at least one voice signal for a user voice acquired by at least one peripheral device .. and a voice signal for the user voice acquired by the video display device; comparing the plurality of acquired voice signals with each other; determining a voice signal subjected to voice recognition based on the comparison result; [0176], The control unit of the video display device may compare qualities of the plurality of acquired voice signals based on at least one of a user voice range level <read on ‘size’> and a noise level of each of the plurality of acquired voice signals).”
Srinivasan in view of TROMPF does not explicitly disclose “a command with the largest size ..” However, the feature is taught by Ganeshkumar (Title: Audio signal processing for noise reduction).
In the same field of endeavor, Ganeshkumar teaches: [0005] “compare the primary signal and the secondary signal, and provide a selected signal based upon the primary signal, the secondary signal, and the comparison” and [0006] “to compare the primary signal and the secondary signal by signal energies <read on size which is subject to BRI>).”
Therefore, it would have been obvious to one of ordinary skill in the art at the time before the effective filing date of the claimed invention to incorporate the teachings of Ganeshkumar in a system (as taught by Srinivasan and TROMPF) to measure the signal energies of the audio signals captured by the primary microphone and the secondary microphone and select the one with the largest energy/size as the user voice to be recognized by voice recognition for any subsequent applications with enhanced accuracy.
6. Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan in view of TROMPF, and further in view of Binder, et al. (US 20140222436; hereinafter BINDER).
As per claim 15 (dependent on claim 1), Srinivasan in view of TROMPF further discloses “compensate the user voice recognition using audio data received from the peripheral device if [ a wakeup word is recognized ] (Srinivasan, [Introduction, para 2-3], use of a remote wireless microphone (RWM) <read on ‘the peripheral device’> placed close to a noise source, which transmits relevant information to the primary device <under any preset condition>, where it is used for noise reduction <read on ‘compensate the user voice recognition’>).”
Srinivasan in view of TROMPF does not explicitly disclose “a wakeup word is recognized ..” However, the feature is taught by BINDER (Title: Voice trigger for a digital assistant).
In the same field of endeavor, BINDER teaches: [0007] “the trigger sound detector recognizes whether a voice input includes a predefined pattern (e.g., a sonic pattern matching the words “Hey, SIRI”) <read on ‘wakeup word’>.”
Therefore, it would have been obvious to one of ordinary skill in the art at the time before the effective filing date of the claimed invention to incorporate the teachings of BINDER in a system (as taught by Srinivasan and TROMPF) to detect and recognize a wakeup word and activate the display device for full-capacity functions and operations, including compensate the voice recognition operation by adding the remote microphone data.
Conclusion
7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to FENG-TZER TZENG whose telephone number is 571-272-4609. The examiner can normally be reached on M-F (9:00-5:00). The fax phone number where this application or proceeding is assigned is 571-273-4609.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Paras Shah (SPE) can be reached on 571-270-1650.
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/FENG-TZER TZENG/ 2/5/2026
Primary Examiner, Art Unit 2653