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 statement (IDS) submitted on 01/29/2025 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-8 and 11-18 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-9 and 11-19 of U.S. Patent No. 11,532,299 (hereinafter ‘299) . Although the claims at issue are not identical, they are not patentably distinct from each other because the claims are obvious variations of each other.
Regarding Claim 1 (drawn to a method):
Current Application
Claim 1:
A computer-implemented method executed on data processing hardware that causes the data processing hardware to perform operations comprising:
receiving the speech input corresponding to a voice query spoken by the user; and
receiving language model biasing parameters comprising a list of certain words;
biasing, using the language model biasing parameters, a language model of an automated speech recognition (ASR) module to increase a likelihood of the ASR module recognizing the certain words in a speech input subsequently provided by a user.
the Asr module comprising an acoustic model and the biased language model;
processing, using the acoustic model and the biased language model of the ASR module, the speech input to generate a transcription of the voice query spoken by the user.
‘299
Claim 1:
A method comprising:
receiving at a user device associated with a user audio data corresponding to a voice query spoken by the user;
processing, by the user device, using a language model, the audio data corresponding to the voice query spoken by the user to determine a particular context associated with biasing the language model, the particular context associated with biasing the language model based on a type of words used in the voice query;
selecting by the user device, a set of biasing terms based on the particular context associated with biasing the language model; and
biasing, by the user device, using the set of biasing terms, the language model to increase a likelihood of recognizing biasing terms from the set of biasing terms in the audio data.
Claim 3:
… further comprising providing, by the user device, the biased language model to an automated speech recognition module, the automated speech recognition module comprising an acoustic model configured to generate readable text from speech inputs spoken by the user.
Claim 9:
… further comprising, after biasing the language model, generating, by the user device, using the biased language model, a transcription of the received audio data corresponding to the voice query spoken by the user.
Regarding Claim 11 (drawn to a system):
Current Application
Claim 11:
A system comprising:
data processing hardware; and
memory hardware in communication with the data processing hardware and storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations comprising:
receiving the speech input corresponding to a voice query spoken by the user; and
receiving language model biasing parameters comprising a list of certain words;
biasing, using the language model biasing parameters, a language model of an automated speech recognition (ASR) module to increase a likelihood of the ASR module recognizing the certain words in a speech input subsequently provided by a user.
the Asr module comprising an acoustic model and the biased language model;
processing, using the acoustic model and the biased language model of the ASR module, the speech input to generate a transcription of the voice query spoken by the user.
‘299
Claim 11:
A user device comprising:
data processing hardware; and
memory hardware in communication with the data processing hardware and storing instructions that when executed on the data processing hard-ware cause the data processing hardware to perform operations comprising:
receiving audio data corresponding to a voice query spoken by a user
processing using a language model, the audio data corresponding to the voice query spoken by the user to determine a particular context associated with biasing the language model, the particular context associated with biasing the language model based on a type of words used in the voice query:
selecting a set of biasing terms based on the particular context associated with biasing the language model; and
biasing, using the set of biasing terms, the language model to increase a likelihood of recognizing biasing terms from the set of biasing terms in the audio data.
Claim 13:
… wherein the operations further comprise providing the biased language model to an automated speech recognition module, the automated speech recognition module comprising an acoustic model configured to generate readable text from speech inputs spoken by the user.
Claim 19:
… wherein the operations further comprise, after biasing the language model, generating, using the biased language model, a transcription of the received audio data corresponding to the voice query spoken by the user.
As shown in the tables above, it is clear that all the elements of the application claims 1 and 11 are to be found in patent claims 1, 3, 9, 11, 13, and 19, as the application claims 1 and 11 fully encompasses patent claims 1, 3, 9, 11, 13, and 19. The difference between the application claims 1 and 11 and the patent claims 1, 3, 9, 11, 13, and 19 lies in the fact that the patent claims includes more elements and is thus more specific. Thus the invention of claims 1, 3, 9, 11, 13, and 19 of the patent is in effect a “species” of the “generic” invention of the application claims 1 and 11. It has been held that the generic invention is “anticipated” by the “species”. See In re Goodman, 29 USPQ2d 2010 (Fed. Cir. 1993).
Claim 2 of the current application corresponds to claim 4 of U.S. Patent No. 11,532,299.
Claim 3 of the current application corresponds to claim 2 of U.S. Patent No. 11,532,299.
Claim 4 of the current application corresponds to claim 4 of U.S. Patent No. 11,532,299.
Claim 5 of the current application corresponds to claim 5 of U.S. Patent No. 11,532,299.
Claim 6 of the current application corresponds to claim 6 of U.S. Patent No. 11,532,299.
Claim 7 of the current application corresponds to claim 7 of U.S. Patent No. 11,532,299.
Claim 8 of the current application corresponds to claim 8 of U.S. Patent No. 11,532,299.
Claim 12 of the current application corresponds to claim 14 of U.S. Patent No. 11,532,299.
Claim 13 of the current application corresponds to claim 12 of U.S. Patent No. 11,532,299.
Claim 14 of the current application corresponds to claim 14 of U.S. Patent No. 11,532,299.
Claim 15 of the current application corresponds to claim 15 of U.S. Patent No. 11,532,299.
Claim 16 of the current application corresponds to claim 16 of U.S. Patent No. 11,532,299.
Claim 17 of the current application corresponds to claim 17 of U.S. Patent No. 11,532,299.
Claim 18 of the current application corresponds to claim 18 of U.S. Patent No. 11,532,299.
Claims 9, 10, 19, and 20 of the current application do not correspond to any claims of U.S. Patent No. 11,532,299.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claims 1 and 11 relate to the statutory category of method/process and machine/apparatus. The independent claims 1 and 11 claims recite “receiving language model biasing parameters comprising a list of certain words; biasing, using the language model biasing parameters, a language model of an automated speech recognition (ASR) module to increase a likelihood of the ASR module recognizing the certain words in a speech input subsequently provided by a user, the Asr module comprising an acoustic model and the biased language model; receiving the speech input corresponding to a voice query spoken by the user; and processing, using the acoustic model and the biased language model of the ASR module, the speech input to generate a transcription of the voice query spoken by the user”.
The limitations of claims 1 or 11 of “receiving…”, “biasing…”, “receiving…”, and “processing” as drafted covers mental activity. More specifically, for claim 1, a human receives guideline related to a list of certain words. The guideline is then used to determine if the probability increases that these words will be used in a vocal query by a user. The input query is then transcribed into textual format of the guideline and the vocal query.
This judicial exception is not integrated into a practical application. In particular, claim 11, recites the additional elements of “data processing hardware” and “memory” which are recited generally in the specification. For example, in paragraph [0056] of the as filed specification, there is a description of using a general purpose operating system. Accordingly, these additional elements don not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claims 1 and 11 recite the additional elements of “language model”, and “acoustic model” which are recited generally in the specification. For example, in paragraph [0031] of the as filed specification, there is a description of using a general purpose operating system to generate a list of restaurants and transcribe the list into textual form. However, the claims are unclear as to what is specifically required by the language model and acoustic mode to generate and transcribe the list. Accordingly, these additional elements don not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element of using a computer is noted as a general computer. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
With regards to claims 2 and 12, the claims relate to determining that the transcription includes at least one word from the guideline. The claims relate to a mental activity of determining that the textual transcription includes words from the guidelines listing certain words to describe the query. No additional limitations are present.
With respect to claims 3 and 13, the claims relate to the guideline is narrowed based on the number of words in the vocal query. The claims relate to a mental activity of narrowing the guideline as the vocal query becomes more specific as more words are used to describe the question. No additional limitations are present.
With respect to claims 4 and 14, the claims relate to determining the context of the query based on the words used. The claims relate to a mental activity of determining what the question is about based the words used in the question. No additional limitations are present.
With respect to claims 5 and 15, the claims relate to getting additional vocal content, determining that once the additional vocal content is received, that the guideline is no longer applicable, and if the guideline is no longer applicable, going back to a baseline state. The claims relate to a mental activity of determining if once additional context is received, that the guideline is no longer appropriate and the context is returned to a basic understanding of the question. No additional limitations are present.
With respect to claims 6 and 16, the claims relate to when determining that the context associated with the guideline is no longer applicable, that the additional vocal content is not related to the context of the original query and is probably related to another query not related to this context. The claims relate to a mental activity of determining when additional vocal content is received and the guideline isn’t appropriate, that the additional content was related to a different question. No additional limitations are present.
With respect to claims 7 and 17, the claims relate to when determining that the context associated with the guideline is no longer applicable, that the confidence in the context doesn’t meet a threshold. The claims relate to a mental activity of determining when additional vocal content is received that the confidence in the context of the question doesn’t meet a threshold. No additional limitations are present.
With respect to claims 8 and 18, the claims relate to where the confidence is related to the likelihood that the context of the query is related to the guideline. The claims relate to a mental activity of determining if the additional vocal content is related to the guideline. No additional limitations are present.
With respect to claims 9 and 19, the claims relate to the computing device being a server in communication with a user. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element of using a computer is noted as a general computer. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. No additional limitations are present.
With respect to claims 10 and 20, the claims relate to capturing the vocal query thru a microphone. The claims relate to a mental activity of speaking into a microphone, The additional limitation of using a microphone is directed to insignificant pre-solution activity to collect speech data.
Allowable Subject Matter
Claims 1-20 would be allowable if the Double Patenting rejections and 35 USC 101 rejections above are overcome.
The following is a statement of reasons for the indication of allowable subject matter: Claims 1 and 11 of the current application teaches similar subject matter as the prior art of Biadsy et al. (US 9,842,592), Aleksic et al. (US 9,502, 032), and Gruber et al. (S 9,858,925). However, the prior art in fails to teach “biasing, using the language model biasing parameters, a language model of an automated speech recognition (ASR) module to increase a likelihood of the ASR module recognizing the certain words in a speech input subsequently provided by a user, the Asr module comprising an acoustic model and the biased language model” as recited in claims 1 and 11.
Claims 2-10 and 12-20 would be allowable for being dependent on an allowable base claim if the Double Patenting rejections and 35 USC 101 rejections above are overcome.
Cited Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Meisel et al. (US 9,495,956) discloses dealing with switch latency in speech recognition.
Salvador et al. (9,153,231) discloses adaptive neural network speech recognition models.
Phillips (US 8,949,130) discloses internal and external speech recognition use with a mobile communication facility.
Meisel et al. (US 8,886,545) discloses dealing with switch latency in speech recognition.
Cerra et al. (US 8,886,540) discloses using speech recognition results based on an unstructured language model in a mobile communication facility applications.
Cerra et al. (US 8,838,457) discloses using results of unstructured language models based speech recognition to control a system-level function of a mobile communication facility.
Phillips et al. (US 8,635,243) discloses sending a communications header with voice recording to send metadata for use in speech recognition, formatting, and search mobile search applications.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SATWANT K SINGH whose telephone number is (571)272-7468. The examiner can normally be reached Monday thru Friday 9:00 AM to 6:00 PM EST.
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/SATWANT K SINGH/Primary Examiner, Art Unit 2653
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