DETAILED ACTION
Introduction
1. A response was filed in this application on 06/11/2026 after the non-final rejection of 03/11/2026. Claims 1-2, 4-9, 11-16 and 18-20 are amended while no claims are cancelled or added in this latest submission by the Applicant. Thus, claims 1-20 are currently pending for reconsideration by the Examiner and are examined below. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to arguments
2. The Applicant’s arguments have been fully considered but they are moot in light of new grounds of rejections as necessitated by amendments.
Response to amendments
3. The rejection under 35 U.S.C. 101 is withdrawn in light of the amendments presented by the Applicant further in view of the arguments presented in this latest submission.
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 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.
4. Claims 1, 8 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Cyr (U.S. Patent Application Publication # 2003/0105623 A1) in view of DiMaria (U.S. Patent Application Publication # 2018/0285455 A1) and further in view of Kamvar (U.S. Patent # 9031216 B1).
With regards to claim 1, Cyr teaches a method comprising receiving, by a computing device one or more audio files (Para 22, teaches receiving speech files);
determining, the one or more audio files, based on characteristics associated with the one or more audio files, to identify at least one audio file of the one or more audio files that requires speech recognition processing to recognize the corresponding voice query (Paragraphs 62-65, teach that user data includes author, context, priority, and identification as to whether dictation is to be used for speech recognition or manual transcription);
prioritizing, based on at least one other characteristic of the at least one identified audio file, the at least one identified audio file relative to other audio files that require speech recognition processing (Paragraphs 28-30, teach that he dynamic monitoring agent and dispatch system work together to insert new jobs into appropriate queues of the speech recognition engines, submit the work based upon priority and bump the priority level up when a job has been sitting around too long. Paragraphs 62-65, teach that user data includes author, context, priority, and identification as to whether dictation is to be used for speech recognition or manual transcription. The user data also includes an acoustic profile of the user. A speech recognition engine wrapper keeps jobs in a queue in order of priority. If a new job is accepted, it will be put at the end of the queue for its priority);
and sending, by the computing device and based on the priority of the at least one identified audio file, the at least one identified audio file for speech recognition processing (Paragraphs 28-30, teach that the dispatch system and dynamic monitoring agent work in conjunction to ensure that speech files are sent to the variety of available speech recognition engines in a manner which optimizes operation of the entire system);
Cyr may not explicitly detail that the aforementioned determining step comprises filtering the one or more audio files, based on characteristics associated with the one or more audio files. This is taught by DiMaria (Para 43, teaches an audio processing machine comprising a candidate search module and a full comparison module. The candidate search module is configured to select, or otherwise determine, a set of candidate audio files from a larger set of audio files to be provided to the full comparison module. The full comparison module is configured to determine the relationship between the set of candidate audio files. The candidate search module reduces the number of audio files to be analyzed and compared, thereby reducing the workload of the full comparison module and consequently, the audio processing machine. Para 45, further teaches that said comparison is performed on the same audio characteristics as Cyr, e.g. comparing the artist name and track name of an audio file with the artist names and track names of the other audio files);
Cyr and DiMaria can be considered as analogous art as they belong to a similar field of endeavor in audio querying. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of DiMaria (Filtering of audio files to be sent for voice query processing) with those of Cyr (Use of speech files for a distributed speech recognition system) to obtain the results as shown above, so as to reduce the number of audio files to be processed thereby reducing the workload of the system of Cyr (DiMaria, para 43).
Cyr also may not explicitly detail the limitation wherein each audio file corresponds to a different voice query. This is taught by Kamvar (Col. 19, line 63 to col. 20, line 24, teach a voice query input by a user over a telephone connection. An audio file of this query is submitted to a voice server for speech recognition);
Cyr, DiMaria and Kamvar can be considered as analogous art as they belong to a similar field of endeavor in audio processing. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of Kamvar (Use of audio files for voice query processing) with those of Cyr and DiMaria to obtain the results as shown above, as it is a very routine design choice that a person with ordinary skill in the art would make to extend the application of the distributed speech recognition system of Cyr to voiced queries as outlined in Kamvar.
With regards to claim 8, this is a CRM claim for the corresponding method claim 1. These two claims are related as method and CRM of using the same, with each claimed CRM element's function corresponding to the claimed method step. Accordingly, claim 8 is similarly rejected under the same rationale as applied above with respect to method claim 1.
With regards to claims 15, this is a system claim for the corresponding method claim 1. These two claims are related as method and system of using the same, with each claimed system element's function corresponding to the claimed method step. Accordingly, claim 15 is similarly rejected under the same rationale as applied above with respect to method claim 1.
5. Claims 2-6, 9-13 and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Cyr in view of DiMaria in further view of Kamvar and further in view of Mallinson (U.S. Patent Application Publication # 2017/0013314 A1).
With regards to claim 2, Cyr and Kamvar may not explicitly detail the limitation wherein filtering the one or more audio files, based on characteristics associated with the one or more audio files, to identify at least one audio file of the one or more audio files that requires speech recognition processing to recognize the corresponding voice query further comprises creating an audio fingerprint of each of the one or more audio files and comparing the each created audio fingerprint to one or more stored audio fingerprints.. This is taught by Mallinson (Para 25 and figure 3, teach that an audio fingerprinting process is used to compare audio information captured by the user with audio information stored in the database);
Cyr, DiMaria, Kamvar and Mallinson can be considered as analogous art as they belong to a similar field of endeavor in audio processing. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of Cyr, DiMaria and Kamvar with those of Mallinson (Use of audio finger print comparison) for identifying, locating, and/or accessing supplemental content or relevant information pertaining to the speech signals of Cyr, DiMaria and Kamvar (Mallinson, para 4).
With regards to claim 3, Cyr, DiMaria and Kamvar may not explicitly detail the limitation wherein the one or more stored audio fingerprints are associated with one or more previously received voice queries. This is again taught by Mallinson (Para 35, teaches that the system can first compare a segment with information in the appropriate database to determine whether if the same, or a substantially similar, segment has previously been identified);
Cyr, DiMaria, Kamvar and Mallinson can be considered as analogous art as they belong to a similar field of endeavor in audio processing. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of Cyr, DiMaria and Kamvar with those of Mallinson (Use of audio finger print comparison) for identifying, locating, and/or accessing supplemental content or relevant information pertaining to the speech signals of Cyr and Kamvar (Mallinson, para 4).
With regards to claim 4, Cyr, DiMaria and Kamvar may not explicitly detail the limitation wherein creating the audio fingerprint of the one or more audio files further comprises creating the audio fingerprint of a randomly selected portion of each of the one or more audios file or a sampling of each of the one or more audio files. This is once again taught by Mallinson (Para 21, teaches that a microphone or other such media capturing element can periodically, continually, or at selected times sample or capture the audio of the broadcast);
Cyr, DiMaria, Kamvar and Mallinson can be considered as analogous art as they belong to a similar field of endeavor in audio processing. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of Cyr, DiMaria and Kamvar with those of Mallinson (Use of audio finger print comparison) for identifying, locating, and/or accessing supplemental content or relevant information pertaining to the speech signals of Cyr and Kamvar (Mallinson, para 4).
With regards to claim 5, Cyr, DiMaria and Kamvar may not explicitly detail the limitation wherein the other characteristic is at least one of a potential revenue associated with the at least one identified audio file, a category of a user associated with the at least one identified audio file, or an indication of a complexity of the at least one identified audio file. This aspect is once again taught by Mallinson (Para 27 and figure 3, teach that the second type of audio files, i.e., for which no match in found via audio fingerprinting, are ranked by a confidence level or score. Further, the threshold of the confidence level or score can be increased or decreased to find a match, e.g., longer and shorter version of the same commercial. These files are then further processed by the increased or decreased threshold of confidence level/score);
Cyr, DiMaria, Kamvar and Mallinson can be considered as analogous art as they belong to a similar field of endeavor in speech processing. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of Cyr, DiMaria and Kamvar with those of Mallinson (Use of audio fingerprint comparison) for identifying, locating, and/or accessing supplemental content or relevant information pertaining to the speech signals of Cyr and Kamvar (Mallinson, para 4).
27102005.023860
With regards to claim 6, Cyr and Kamvar may not explicitly detail the limitation of generating a response to the corresponding voice query of the at least one identified audio file. This aspect is once again taught by Mallinson (Para 26 and figure 3, further teach that files in which matched is found based on audio fingerprinting can return the results to the user as supplemental content);
Cyr, DiMaria, Kamvar and Mallinson can be considered as analogous art as they belong to a similar field of endeavor in speech processing. It would thus have been obvious to one having ordinary skill in the art to advantageously combine the teachings of Cyr, DiMaria and Kamvar with those of Mallinson (Use of audio fingerprint comparison) for identifying, locating, and/or accessing supplemental content or relevant information pertaining to the speech signals of Cyr and Kamvar (Mallinson, para 4).
With regards to claims 9-13, these are computer readable medium (CRM) claims for the corresponding method claims 2-6. These two sets of claims are related as method and CRM of using the same, with each claimed CRM element's function corresponding to the claimed method step. Accordingly, claims 9-13 are similarly rejected under the same rationale as applied above with respect to method claims 2-6.
With regards to claims 16-19, these are system claims for the corresponding method claims 2-5. These two sets of claims are related as method and system of using the same, with each claimed system element's function corresponding to the claimed method step. Accordingly, claims 16-19 are similarly rejected under the same rationale as applied above with respect to method claims 2-5.
Allowable Subject Matter
6. Claims 7, 14 and 20 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. The prior art of record, alone or in combination, does not currently suggest or teach the invention as outlined in these claims. More detailed reasons for allowance will be outlined as and when the Application goes to allowability.
Conclusion
7. 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). The Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). The following prior art, made of record but not relied upon, is considered pertinent to applicant's disclosure: Romano (U.S. Patent Application Publication # 2014/0222419 A1), Van (U.S. Patent Application Publication # 2014/0100853 A1). These references are also included in the PTO-892 form attached with this office action.
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 extension fee 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 date of this final action.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to NEERAJ SHARMA whose contact information is given below. The examiner can normally be reached on Monday to Friday 8 am to 5 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre Louis-Desir can be reached on 571-272-7799 (Direct Phone). The fax number for the organization where this application or proceeding is assigned is 571-273-8300.
/NEERAJ SHARMA/
Primary Examiner, Art Unit 2659
571-270-5487 (Direct Phone)
571-270-6487 (Direct Fax)
neeraj.sharma@uspto.gov (Direct Email)
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