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 .
DETAIL ACTION
Priority
This application claims priority to U.S provisional Patent Application No. 63390739, filed on 7/20/2022 and is hereby incorporated by references.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 12/9/2024 and 5/19/2026. The submission 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
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, 5-12 and 16-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Takiel (US 20180189267 A1) in view of Sukumar (US 20210358496 A1).
Regarding claim 1, Takiel discloses a method [e.g. FIG. 1 and 8] comprising causing a voice assistant [e.g. human to computer dialog] and a recommendation engine [e.g. dialog context engine 150] that are executing in an infotainment system of a vehicle [e.g. FIG. 1 and 8-9; [0035]; e.g. an in-vehicle entertainment system] to cooperate in processing a user’s acceptance of a recommendation [e.g. an answer from dialog context engine] proposed by said recommendation engine, wherein causing said voice assistant and said recommendation engine to cooperate comprises:
causing said recommendation engine to provide a recommendation to a recommendation interface that is between said voice assistant and said recommendation engine, said recommendation comprising a recommendation context [e.g. FIG. 1 and 8; [0046]; contextual data structure 152, automated assistant 120 is able to interpret natural language input from the user that is unrelated to the most recent topic of discussion, and thus is better able to adapt to the user changing the subject of the human-to-computer dialog],
receiving, by said voice assistant, an utterance from said user [e.g. [0061]; the user asks “who built it” when the user stands in front of the Eiffel Tower], wherein said utterance indicates acceptance of an unidentified recommendation [e.g. based on point_of_interest; Automated assistant 120 may apply the above grammar rule to parse the user's natural language input], causing said voice assistant to identify an action [e.g. [0061-0062]; proving an answer “The Eiffel Tower was built by Gustave Eiffel.”] to be carried out based at least in part on said recommendation context and said utterance, and
causing said voice assistant to carry out said action [e.g. returning an answer].
It is noted that Takiel differs to the present invention in that Takiel fails to explicitly disclose a vehicle occupant.
However, Sukumar teaches the well-known concept of a voice assistant and a recommendation engine [e.g. voice assistant and computing system] that are executing in an infotainment system of a vehicle [e.g. FIG. 1; [0063]; 22; e.g. an infotainment system] to cooperate in processing a vehicle occupant's acceptance of a recommendation [e.g. [0052]; a vehicle occupant; FIG. 3; an answer from dialog management] proposed by the recommendation engine; receiving, by the voice assistant, an utterance from said occupant [e.g. FIG.3-4; [0064]; the utterance of the user 10, e.g., the voice input].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 5, Takiel and Sukumar disclose a data structure and wherein said method further comprises causing said voice assistant to infer an intent of said occupant based at least in part on said data structure and said utterance [e.g. Takiel: FIG. 1-2; [0046]; data structure; Sukumar: FIG. 1-3; [0081-0082]].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 6, Takiel and Sukumar disclose said recommendation context comprises a JSON data structure and wherein said method further comprises causing said voice assistant to infer an intent of said occupant based at least in part on said JSON data structure and said utterance [e.g. Sukumar: FIG. 1-3; [0081-0082]; JSON data structure].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 7, Takiel and Sukumar disclose said recommendation context comprises values of variables from context data that is used by said recommendation engine to propose a recommendation [e.g. Takiel: FIG. 1-2; [0046-0047]; Sukumar: FIG. 1-3 and 5; user context data, e.g. number of vehicle occupants, an itinerary of the user etc] .
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 8, Takiel and Sukumar disclose causing said recommendation engine to monitor context data and to propose said recommendation based at least in part on said context data [e.g. Takiel: FIG. 1-2; [0046-0047]; Sukumar: FIG. 1-3 and 5].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 9, Takiel and Sukumar disclose monitor context data and to propose said recommendation based at least in part on said context data [e.g. Takiel: FIG. 1-2 and 8; Sukumar: FIG. 1-3 and 5; context data e.g. sensor data], wherein said context data comprises vehicle sensor data [Sukumar: sensor data], application event data e.g. Takiel: FIG. 1; Sukumar: FIG. 1 and 4-5], content data [e.g. content of the natural language], OEM data [e.g. Sukumar: FIG. 1 and 4-5; [0080]], and occupant data [e.g. Sukumar: FIG. 1 and 4-6], wherein said vehicle sensor data, which is obtained from sensors in said vehicle [e.g. Sukumar: FIG. 1 and 4-5; [0065]; sensors], comprises data that is indicative of an operating state of said vehicle [e.g. Sukumar: FIG. 1 and 4-5], wherein said application event data comprises data that is indicative of state and history of applications executing on said infotainment system [e.g. Takiel: FIG. 1 and 6-7; Sukumar: FIG. 1 and 3-4], wherein said content data comprises data indicative of media content [e.g. Takiel: FIG. 1 and 5], wherein OEM service data comprises information indicative of car maintenance events [e.g. Sukumar: FIG. 1 and 4-5; [0080 and 0146]], and wherein occupant data comprises information concerning said occupant [e.g. Sukumar: FIG. 1 and 4-6].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 10, Takiel and Sukumar disclose a prompt and wherein said method further comprises causing said voice assistant to communicate said recommendation to said occupant by uttering said prompt [e.g. Takiel: FIG. 1 and 8; [0041]; prompt; Sukumar: FIG. 1-3].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 11, Takiel and Sukumar disclose a context-dependent response, wherein said context- dependent response comprises what said occupant would be expected to utter as a response to a prompt that communicates said recommendation to said occupant, wherein said context-dependent response indicates that an action is to be carried out, and wherein said context-dependent response omits an identification of said action [e.g. Takiel: FIG. 1 and 8; [0071-0073]; providing response dependent to contextual data; Sukumar: FIG. 1-3 and 5; providing a suggested action based on context].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]].
Regarding claim 12 and 16-22, this is an apparatus that includes same limitation as in claim 1 and 5-11above, the rejection of which are incorporated herein.
Claim(s) 2-4 and 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Takiel (US 20180189267 A1) in view of Sukumar (US 20210358496 A1) and Debnath et al (US 20200058295 A1).
Regarding claim 2, Takiel and Sukumar disclose said recommendation context comprises a natural language command that, when uttered by said occupant, would cause said voice assistant to carry out said action [e.g. Takiel: FIG. 1-2 and 6; natural language input; Sukumar: FIG. 1-3], but Takiel and Sukumar fail to explicitly disclose the detail of the command.
However, Debnath causing a voice assistant [e.g. FIG. 1] to carry out an action [e.g. reply] comprises causing said voice assistant to carry out said action without said occupant having uttered said command [e.g. [0010 and 0085]; the virtual agent respond; TABLE 7; AD006].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar and the well-known detecting partial utterances technique taught by Debnath as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]] and improved the virtual agent's ability to determine and deliver what it is the user desires [See Debnath; [0010]].
Regarding claim 3, Takiel, Sukumar and Debnath disclose said recommendation context comprises a natural language command and wherein causing said voice assistant to carry out said action comprises causing said voice assistant to substitute said natural language command for said utterance from said occupant [e.g. Takiel: FIG. 1-2; Sukumar: 1-3; Debnath: [0010 and 0085]; the virtual agent respond; TABLE 7].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the human-to-computer dialog system disclosed by Takiel to exploit the well-known voice assistant for a vehicle technique taught by Sukumar and the well-known detecting partial utterances technique taught by Debnath as above, in order to provide improved performance of the voice assistant systems [See Sukumar; [0095 and 0149]] and improved the virtual agent's ability to determine and deliver what it is the user desires [See Debnath; [0010]].
Regarding claim 4, Takiel, Sukumar and Debnath disclose said voice assistant using said natural language command and said utterance as a basis for inferring an intent of said occupant [e.g. Takiel: FIG. 1-2; the user's true intention; Sukumar: 1-3; The intent parser 48; Debnath: FIG. 3; [0009 and 0045]].
Regarding claim 13-15, this is an apparatus that includes same limitation as in claim 2-4 above, the rejection of which are incorporated herein.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
GRAHAM et al (US 20180336275 A1).
KARP et al (US 20230353674 A1).
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/ZHUBING REN/ Primary Examiner, Art Unit 2658
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