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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Copy of priority document has been electronically retrieved by USPTO on 02/25/2026.
Response to Amendment
Rejection presented against claims 11 and 12 under 35 USC 101 has been withdrawn in response to claims getting cancelled on 01/08/2026.
Response to Arguments
Applicant's arguments filed 01/08/2026 have been fully considered but they are not persuasive. Although no arguments are presented for a specific limitations, examiner will address limitations added to claim 1 to clarify rationale for rejection.
Burke teaches all the limitations of claim 1 except training, by a system comprising a processor, during operation of a specific vehicle, using audio data captured from the specific vehicle, a machine learning model to learn to identify seat locations of occupants of the specific vehicle based on an arrangement of one or more audio recording devices in the specific vehicle and an interior design defining an acoustic behavior inside the specific vehicle
Jain teaches training, by a system comprising a processor, during operation of a specific vehicle, using audio data captured from the specific vehicle, a machine learning model to learn to identify seat locations of occupants of the specific vehicle based on an arrangement of one or more audio recording devices in the specific vehicle and an interior design defining an acoustic behavior inside the specific vehicle ([0074], disclosing an advanced computing platform running a plurality of neural networks, computer vision and speech algorithms. [0163], disclosing advanced AI-assisted vehicle includes a passenger interface for communicating with passengers, speech recognition. [0082], disclosing vehicle collects data that is preferably used to help train and refine the neural networks used for occupant monitoring. [0088], disclosing neural networks preferably are trained to detect a number of different features and events, including: the identity of a person in the driver’s seat or one or more passenger seats, whether the driver is speaking, and, if so, what the driver is saying (by audio input or lip-reading). Audio is necessarily captured through one or more audio recording devices and it is necessarily affected by acoustic behavior inside the vehicle. And acoustic behavior is necessarily defined by interior design of vehicle e.g., outside noise isolation, sound absorbing material inside cabin, echo produced etc.)
Burke and Jain are analogous arts as they are in same field of endeavor i.e., speech recognition.
It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Burke to training, by a system comprising a processor, during operation of a specific vehicle, using audio data captured from the specific vehicle, a machine learning model to learn to identify seat locations of occupants of the specific vehicle based on an arrangement of one or more audio recording devices in the specific vehicle and an interior design defining an acoustic behavior inside the specific vehicle as taught by Jain to train and improve accuracy of speech recognition system.
As modification through Jain addresses Burke’s deficiencies, rejection of claims 1 and 13 is maintained.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 5, 7-10, 13, 17, 19, 20 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Burke (US 20220016999) in view of Jain (US 20230356728).
For claim 1, Burke teaches: A method comprising:
receiving, by the system, current audio data based on speech of an occupant inside the vehicle ([0020], disclosing audio sensor to detect a person’s identity and position within a vehicle. And performing voice recognition. Hence audio sensor necessarily receives audio data abased on speech of occupant. [0029], disclosing a processor of computing system);
identifying, by the system, a seat location of the occupant inside the specific vehicle based on the received current audio data ([0020], disclosing identifying seat position of a person within a vehicle based on audio data);
identifying, by the system, an occupant settings profile indicative of one or more occupant settings of the specific vehicle for the occupant based on a comparison of the current audio data with stored audio data associated with different occupant settings profiles ([0020], disclosing performing voice recognition for identity determination. Therefore, received audio data is compared with stored occupant profile. [0012], disclosing each user has an independent profile. [0030-0032], disclosing user settings. Hence user profile is identified through voice recognition is compared with stored used profiles to fetch correct profile settings); and
providing, by the system, a control instruction for controlling at least one occupant setting for the identified seat location of the occupant based on the identified occupant settings profile (abstract, disclosing seat or position of the user is determined and settings are applied depending on the which seat is occupied by the user. [0032], disclosing settings include temperature settings, video settings, seat adjustments, audio settings, privacy settings, or other settings for configuring a vehicle).
Although detecting a person’s identity and seat location through speech (disclosed in [0020]) necessitates training a system with audio data captured from the vehicle. Burke does not explicitly disclose it. Therefore, Burke does not explicitly teach: training, by a system comprising a processor, during operation of a specific vehicle, using audio data captured from the specific vehicle, a machine learning model to learn to identify seat locations of occupants of the specific vehicle based on an arrangement of one or more audio recording devices in the specific vehicle and an interior design defining an acoustic behavior inside the specific vehicle
Jain teaches training, by a system comprising a processor, during operation of a specific vehicle, using audio data captured from the specific vehicle, a machine learning model to learn to identify seat locations of occupants of the specific vehicle based on an arrangement of one or more audio recording devices in the specific vehicle and an interior design defining an acoustic behavior inside the specific vehicle ([0074], disclosing an advanced computing platform running a plurality of neural networks, computer vision and speech algorithms. [0163], disclosing advanced AI-assisted vehicle includes a passenger interface for communicating with passengers, speech recognition. [0082], disclosing vehicle (50) may send and/or receive a wide variety of data to the wireless network. For example, vehicle (50) collects data that is preferably used to help train and refine the neural networks used for self-driving and occupant monitoring. [0088], disclosing neural networks preferably are trained to detect a number of different features and events, including: the identity of a person in the driver’s seat or one or more passenger seats, whether the driver is speaking, and, if so, what the driver is saying (by audio input or lip-reading). Neural network is subset of machine learning, audio is necessarily captured through one or more audio recording devices and it is necessarily affected by acoustic behavior inside the vehicle. And acoustic behavior is necessarily defined by interior design of vehicle e.g., outside noise isolation, sound absorbing material inside cabin, echo produced etc.)
Burke and Jain are analogous arts as they are in same field of endeavor i.e., speech recognition.
It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Burke to training, by a system comprising a processor, during operation of a specific vehicle, using audio data captured from the specific vehicle, a machine learning model to learn to identify seat locations of occupants of the specific vehicle based on an arrangement of one or more audio recording devices in the specific vehicle and an interior design defining an acoustic behavior inside the specific vehicle as taught by Jain to train and improve accuracy of speech recognition system.
Claim 13 recites limitations similar in scope to claim 1, hence is similarly rejected.
Claim 21 recites limitations similar in scope to claim 1, hence is similarly rejected.
For claim 5, modified Burke teaches: The method of claim 1, wherein the stored audio data comprises an audio profile of the occupant generated by the trained machine learning model (0020], disclosing performing voice recognition for identity determination. Therefore, received audio data is compared with stored occupant profile. And modification through Jain would generate profile generated by the artificial intelligence model).
Claim 17 recites limitations similar in scope to claim 5, hence is similarly rejected.
For claim 7, modified Burke teaches: The method of claim 1, wherein the identifying of the seat location of the occupant comprises signal processing of the current audio data (0020], disclosing identifying seat position of a person within a vehicle based on audio data. Audio data signal is necessarily processed to identify seat position).
Claim 19 recites limitations similar in scope to claim 7, hence is similarly rejected.
For claim 8, modified Burke teaches: The method of claim 1, wherein the control instruction is configured for controlling at least one comfort setting for the identified seat location ([0032], disclosing settings include temperature settings, video settings, seat adjustments, audio settings, privacy settings, or other settings for configuring a vehicle).
Claim 20 recites limitations similar in scope to claim 8, hence is similarly rejected.
For claim 9, modified Burke teaches: The method of claim 8, wherein the at least one comfort setting comprises at least one of: a temperature setting, a sound setting, or a seat position ([0032], disclosing settings include temperature settings, video settings, seat adjustments, audio settings, privacy settings, or other settings for configuring a vehicle).
For claim 10, modified Burke teaches: The method of claim 1, wherein the control instruction is configured for controlling at least one driver setting for a driver seat location as the identified seat location ([0008], disclosing identifying occupant to be driver. [0017], disclosing vehicle control 149 may be a climate control, display control, volume control, video selector, audio selector, seat control, privacy control, or other controls used to customize the driving experience)
Claims 2, 3, 14, 15, 22 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Burke in view of Jain and Omasta (US 20210129858).
For claim 2, modified Burke teaches: The method of claim 1, further comprising:
Burke does not teach: requesting, by the system, confirmation by the occupant before providing the control instruction.
Omasta teaches requesting, by the system, confirmation by the occupant before providing the control instruction (abstract, disclosing Systems, methods and computer program products that facilitate driver assist interface in a vehicle. [0029], disclosing monitoring component 108 can identify frequent drivers of a vehicle based upon profiles created by the monitoring component. The monitoring component 108 can ask or confirm the identity of a driver using prompts in the vehicle's touch screen controls.
Omasta and Burke are analogous arts as they are in same field of endeavor i.e., driver assist features. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Burke to requesting, by the system, confirmation by the occupant before providing the control instruction to inform the driver of profile being adapted.
Claims 14 and 22 recite limitations similar in scope to claim 2, hence are similarly rejected.
For claim 3, modified Burke teaches: The method of claim 2, wherein the confirmation is requested when a current occupant setting does not correspond to the identified occupant settings profile (setting change is only necessary when current occupant setting does not correspond to the identified occupant settings profile, otherwise no setting change is necessary).
Claims 15 and 23 recite limitations similar in scope to claim 3, hence are similarly rejected.
Claims 6 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Burke in view of Jain and Coon (US 20090055178).
For claim 6, modified Burke teaches: The method of claim 1,
Burke does not disclose: wherein the current audio data is based on a conversation between two or more occupants inside the specific vehicle.
Coon teaches wherein the current audio data is based on a conversation between two or more occupants inside the specific vehicle ([0040], disclosing occupant detection systems may be employed. Voice-based speaker identification software may be used to differentiate users in different locations within the vehicle during normal conversation. Based on the identified speaker location, identity and speech commands, personalized feature settings can be applied to systems and devices to accommodate passengers in each zone of the vehicle)
Burke and Coon are analogous arts as they are in same field of endeavor i.e., identifying users through speech. It would have been obvious to one having ordinary skill in the art before effective filing date of claimed invention to modify art of Burke to wherein the current audio data is based on a conversation between two or more occupants inside the specific vehicle as taught by Coon to enhance user experience and simplify recognition process.
Claim 18 recites limitations similar in scope to claim 6, hence is similarly rejected.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARSLAN AZHAR whose telephone number is (571)270-1703. The examiner can normally be reached Mon-Fri 7:30 - 5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Wade Miles can be reached at (571) 270-7777. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ARSLAN AZHAR/Examiner, Art Unit 3656
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