DETAILED ACTION
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 .
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).
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Claims 2 – 23 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 - 22 of U.S. Patent No.12,154,570. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 2 – 23 of the instant application are similar in scope and content of the claims of the cited US patent.
It would have been obvious to an artisan at the time the invention was made to use the teaching of claims 1 - 22 of the '570' Patent as a general teaching for detecting proper names spans, to perform method as claimed in the present invention. The instant claims obviously encompass the claimed invention of the '570' Patent and differ only in the method steps. The extent that the instant claims are broaden and therefore generic to claimed invention of '570' Patent [species], In re Goodman 29 USPQ 2d 2010 CAFC 1993, states that a generic claim cannot be issued without a terminal disclaimer, if a species claim has been previously been claimed in a co- pending application. And since the structure is as recited, the method step is obtained and therefore, obvious.
Here is a comparison between claim 3 of the instant application and claim 1 of the cited patent (12,154,570).
Instant Application 18/957,924
Cited patent 12,154,570
Comparison
3. A method performed by an electronic computing device, the method comprising:
1. A method performed by a client device, the method comprising:
Similar
sending a copy of a digital representation of an utterance to a computer system via a network;
storing, in memory, a first copy of a digital representation of a spoken utterance; sending a second copy of the digital representation to a computer system via a network;
Similar
receiving, from the computer system,
(i) a first transcription of the utterance, and
(ii) an indication of an acoustic span that includes a proper name and that is representative of a portion of the copy of the digital representation;
identifying a portion of the digital representation that corresponds to the acoustic span;
receiving, from the computer system, an indication of -
(i) a primary transcription of the second copy of the digital representation,
(ii) a proper name present in the second copy of the digital representation, and
(iii) an acoustic span that includes the proper name;
Similar
adapting the speech recognizer based on information that is derived from the first transcription, a physical location of the electronic computing device, or a preference of a user of the electronic computing device.
adapting a speech recognizer using information that is derived from the primary transcription, a physical location of the client device, or a preference of a user of the client device;
Similar
providing at least the portion of the digital representation to a speech recognizer that produces, as output, a second transcription; and
providing at least the acoustic span in the first copy of the digital representation to the speech recognizer that produces, as output, a secondary transcription for the acoustic span; and
Similar
attributing a meaning to the utterance based on an analysis of the first and second transcriptions.
attributing a meaning to the digital representation of the spoken utterance based on an analysis of the primary and secondary transcriptions.
Similar
Claim Rejections - 35 USC § 103
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.
Claims 2, 4 – 8, 18 – 23 are rejected under 35 U.S.C. 103 as being unpatentable Abrams et al. (US PAP 2014/0019126) in view of Griggs et al. (US PAP 2011/0125499).
As per claim 2, Abrams et al. teach a method performed by an electronic computing device, the method comprising:
sending a copy of a digital representation of an utterance to a computer system via a network ("user speech.. on a remote computer or entirely on the remote computer or server": paragraphs 3, 30);
receiving, from the computer system, (i) a first transcription of the utterance, and
identifying a portion of the digital representation that corresponds to the acoustic span; providing at least the portion of the digital representation to a speech recognizer that produces, as output, a second transcription ("updating the word dictionary by temporarily adding words from the location data to the word dictionary; and using the updated word dictionary to convert the previously unrecognized portion of the speech to text."; paragraphs 3, 13); and
attributing a meaning to the utterance based on an analysis of the first and second transcriptions ("The speech-to-text recognizer 30 utilizes word dictionary 34 to attempt to recognize the speech."; paragraphs 13 - 20).
However, Abrams et al. do not specifically teach an indication of an acoustic span that includes a proper name and that is representative of a portion of the copy of the digital representation.
Griggs et al., disclose that word lattice 108 represents one or more possibilities for words that may occur in audio stream 101 at particular times. Each possible word included in word lattice 108 is associated with a start time t-sub.1, an end time t.sub. 2, and a confidence score representative of the probability that the word is a correct match to the word spoken between time t.sub.1 and time t.sub.2 in audio stream 101. Word recognition engine 104 may identify multiple possible words for a given time period or for overlapping time periods, each possible word having a different confidence score... the new word may be a proper name, a word or phrase in a foreign language, a word or phrase related to a current event or recently identified technical problem, or the name of a product or promotion... words potting engine 124 searches audio data 102 to determine time intervals for putative occurrences 125 of the new word in audio stream 101 (paragraphs 21 - 24).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect spoken proper name as taught by Griggs et al. in Abrams et al., because that would help provide an improved method and
system for performing speech-to-text recognition of non-dictionary words (Abrams et al., paragraph 2).
As per claim 4, Abrams et al. in view of Griggs et al. further disclose an indication of a nominal meaning of the utterance is further received from the computer system, and wherein said attributing is representative of a reinterpretation of the utterance with the meaning attributed to the utterance replacing the nominal meaning("in response to a portion of the speech being unrecognizable, determining if the speech contains a location-based phrase that contains a term relating to any combination of a geographic origin or destination, a current location, and a route'; Abrams et al., paragraph 3).
As per claim 5, Abrams et al. in view of Griggs et al. further disclose the first transcription comprises transcribed words, in sequential order, with associated timings, and wherein the acoustic span is defined by a start-of-span word in the first transcription and associated onset of start-of-span word time that defines a start of the acoustic span and an end-of-span word in the first transcription and associated terminus of end-of-span word time that defines an end of the acoustic span ("Each possible word included in word lattice 108 is associated with a start time t-sub.1, an end time t.sub. 2, and a confidence score representative of the probability that the word is a correct match to the word spoken between time t.sub.1 and time t.sub.2 in audio stream 101. Word recognition engine 104 may identify multiple possible words for a given time period or for overlapping time periods, each possible word having a different confidence score"; Griggs et al. paragraphs 21 – 24, see also Abrams et al. paragraph 25).
As per claim 6, Abrams et al. in view of Griggs et al. further disclose the onset of start-of-span word time and the terminus of end-of-span word time are used to identify the portion of the digital representation that corresponds to the acoustic span and for which the second transcription is produced (Griggs et al. paragraphs 21 - 24).
As per claim 7, Abrams et al. in view of Griggs et al. further disclose incorporating the second transcription produced for the portion of the digital representation that corresponds to the acoustic span into the first transcription of the utterance ( Abrams et al., "updating the word dictionary by temporarily adding words from the location data to the word dictionary; and using the updated word dictionary to convert the previously unrecognized portion of the speech to text."; paragraphs 3, 13).
As per claim 8, Abrams et al. in view of Griggs et al. further disclose an indication of a type of the proper name is further received from the computer system, and wherein the method further comprises: selecting, based on the type of the proper name, the speech recognizer from among a plurality of speech recognizers ("the location- phrase detector 42 may be configured to recognize geographic origin and destination phrases in the speech 21, such as "I'm coming from'/"I'm leaving from/the'/"Im on my way to'/"'m heading towards"/I'm meeting [someone/person's name] at", and the like. The location-phrase detector 42 may be further configured to recognize current location phrases when terms are detected in the speech 21, such as "I'm near'/"I'm right beside'/"I'm next two'/"passing by'/and the like. The location- phrase detector 22 may be further configured to recognize route phrases when terms are detected in the speech 21, such as "I'm traveling [direction] [on/along][highway or street name]'/"turning [right/left] on''/and the like."; Abrams et al. paragraph 19).
As per claim 18, Abrams et al. teach a non-transitory medium with instructions stored thereon that, when executed by a processor of an electronic computing device, cause the electronic computing device to:
receive input that is indicative of a request to attribute a meaning to speech for which a digital representation is available("user speech.. on a remote computer or entirely on the remote computer or server": paragraphs 3, 30);
acquire, from a source external to the electronic computing device, a transcription that is determined through recognition of words in a first copy of the digital representation; perform speech recognition on at least a portion of a second copy of the digital representation that corresponds to the acoustic span, so as to produce a second interpretation of the acoustic span ("updating the word dictionary by temporarily adding words from the location data to the word dictionary; and using the updated word dictionary to convert the previously unrecognized portion of the speech to text."; paragraphs 3, 13); and
attribute the meaning to the speech based on an analysis of the transcription with the second interpretation of the acoustic span replacing the first interpretation of the acoustic span ("The speech-to-text recognizer 30 utilizes word dictionary 34 to attempt to recognize the speech."; paragraphs 13 - 20).
However, Abrams et al. do not specifically teach a transcription and that includes a first interpretation of an acoustic span that includes a proper name.
Griggs et al., disclose that word lattice 108 represents one or more possibilities for words that may occur in audio stream 101 at particular times. Each possible word included in word lattice 108 is associated with a start time t-sub.1, an end time t.sub. 2, and a confidence score representative of the probability that the word is a correct match to the word spoken between time t.sub.1 and time t.sub.2 in audio stream 101. Word recognition engine 104 may identify multiple possible words for a given time period or for overlapping time periods, each possible word having a different confidence score... the new word may be a proper name, a word or phrase in a foreign language, a word or phrase related to a current event or recently identified technical problem, or the name of a product or promotion... words potting engine 124 searches audio data 102 to determine time intervals for putative occurrences 125 of the new word in audio stream 101 (paragraphs 21 - 24).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect spoken proper name as taught by Griggs et al. in Abrams et al., because that would help provide an improved method and
system for performing speech-to-text recognition of non-dictionary words (Abrams et al., paragraph 2).
As per claim 19, Abrams et al. in view of Griggs et al. further disclose the instructions further cause the electronic computing device to: transmit the first copy of the digital representation to the source external to the electronic computing device (Abrams et al. paragraphs 13- 25).
As per claim 20, Abrams et al. in view of Griggs et al. further disclose the speech is received by a software application that is configured to search for content based on the meaning attributed to the speech (Abrams et al. paragraphs 13- 25).
As per claim 21, Abrams et al. in view of Griggs et al. further disclose the instructions further cause the electronic computing device to: identify a start-of-span word in the transcription and associated onset of start-of-span word time that defines a start of the acoustic span; identify an end-of-span word in the transcription and associated terminus of end-of-span word time that defines an end of the acoustic span; and excerpt the portion of the second copy of the digital representation based on the onset of start-of- span word time and the terminus of end-of-span word time; and
wherein speech recognition is performed on only the portion of the second copy of the digital representation ("Each possible word included in word lattice 108 is associated with a start time t-sub.1, an end time t.sub. 2, and a confidence score representative of the probability that the word is a correct match to the word spoken between time t.sub.1 and time t.sub.2 in audio stream 101. Word recognition engine 104 may identify multiple possible words for a given time period or for overlapping time periods, each possible word having a different confidence score"; Griggs et al. paragraphs 21 – 24, see also Abrams et al. paragraph 25).
As per claim 22, Abrams et al. in view of Griggs et al. further disclose speech recognition is performed on an entirety of the second copy of the digital representation; and wherein the instructions further cause the electronic computing device to: extract the second interpretation of the acoustic span from a second transcription of the entirety of the second copy of the digital representation (Abrams et al. paragraphs 3, 13, 25).
As per claim 23, Abrams et al. in view of Griggs et al. further disclose the second interpretation of the acoustic span is identified, within the second transcription, based on (i) an onset of start- of-span word time of a start-of-span word in the transcription that defines a start of the acoustic span and (ii) a terminus of end-of-span word time of an end-of-span word in the transcription that defines an end of the acoustic span, and wherein the onset of start-of- span word time and the terminus of end-of-span word time accompany the transcription acquired from the source external to the electronic computing device ("Each possible word included in word lattice 108 is associated with a start time t-sub.1, an end time t.sub. 2, and a confidence score representative of the probability that the word is a correct match to the word spoken between time t.sub.1 and time t.sub.2 in audio stream 101. Word recognition engine 104 may identify multiple possible words for a given time period or for overlapping time periods, each possible word having a different confidence score"; Griggs et al. paragraphs 21 – 24, see also Abrams et al. paragraph 25).
Claims 3, 10 - 17 are rejected under 35 U.S.C. 103 as being unpatentable over Abrams et al. (US PAP 2014/0019126) in view of Griggs et al. (US PAP 2011/0125499); and further in view of Endo et al. (US Patent 7,328,155).
As per claims 3, Abrams et al. in view of Griggs et al. do not specifically teach adapting the speech recognizer based on information that is derived from the first transcription, a physical location of the electronic computing device, or a preference of a user of the electronic computing device.
Endo et al. disclose that other types of information such as the user's home address, habits, preferences, and the like may also be stored in memory in the speech recognition system of the present invention and used to modify the second pass results (col.13, lines 38 – 42).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the speech recognizer based on a preference of a user of the electronic computing device as taught by Endo et al. in Abrams et al. in view of Griggs et al., because that would help provide accurate speech recognition results (col.2, lines 51, 52).
As per claim 10, Abrams et al. teach a method performed by an electronic computing device that is associated with an individual, the method comprising:
receiving, from a source external to the electronic computing device (paragraphs 3, 30);
(ii) a transcription, determined through recognition of words in the first copy of the digital representation, that includes a first interpretation of the acoustic span("updating the word dictionary by temporarily adding words from the location data to the word dictionary; and using the updated word dictionary to convert the previously unrecognized portion of the speech to text."; paragraphs 3, 13);
identifying a portion of a second copy of the digital representation that corresponds to the acoustic span; and providing at least the portion of the second copy of the digital representation to the speech recognizer that produces, as output, a second interpretation ("The speech-to-text recognizer 30 utilizes word dictionary 34 to attempt to recognize the speech… updating the word dictionary by temporarily adding words from the location data to the word dictionary; and using the updated word dictionary to convert the previously unrecognized portion of the speech to text."; paragraphs 3, 13 - 20).
However, Abrams et al. do not specifically teach an indication of an acoustic span that includes a proper name determined to be present in a first copy of a digital representation of an utterance; adapting a speech recognizer based on either (a) linguistic information that is derived from the transcription or a previously decoded utterance or (ii) non-linguistic information that is associated with the electronic computing device or the individual.
Griggs et al., disclose that word lattice 108 represents one or more possibilities for words that may occur in audio stream 101 at particular times. Each possible word included in word lattice 108 is associated with a start time t-sub.1, an end time t.sub. 2, and a confidence score representative of the probability that the word is a correct match to the word spoken between time t.sub.1 and time t.sub.2 in audio stream 101. Word recognition engine 104 may identify multiple possible words for a given time period or for overlapping time periods, each possible word having a different confidence score... the new word may be a proper name, a word or phrase in a foreign language, a word or phrase related to a current event or recently identified technical problem, or the name of a product or promotion... words potting engine 124 searches audio data 102 to determine time intervals for putative occurrences 125 of the new word in audio stream 101 (paragraphs 21 - 24).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect spoken proper name as taught by Griggs et al. in Abrams et al., because that would help provide an improved method and
system for performing speech-to-text recognition of non-dictionary words (Abrams et al., paragraph 2).
However, Abrams et al. in view of Griggs et al. do not specifically teach adapting a speech recognizer based on either (a) linguistic information that is derived from the transcription or a previously decoded utterance or (ii) non-linguistic information that is associated with the electronic computing device or the individual.
Endo et al. disclose that other types of information such as the user's home address, habits, preferences, and the like may also be stored in memory in the speech recognition system of the present invention and used to modify the second pass results (col.13, lines 38 – 42).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to adapt the speech recognizer based on a preference of a user of the electronic computing device as taught by Endo et al. in Abrams et al. in view of Griggs et al., because that would help provide accurate speech recognition results (col.2, lines 51, 52).
As per claim 11, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose adapting comprises expanding the speech recognizer by adding one or more words to an existing vocabulary used for transcription, so as to ensure that the one or more words are considered by the speech recognizer in producing the second interpretation (Endo et al. col.13, lines 38 – 42; Abrams et al. paragraphs 3, 13 - 20).
As per claim 12, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose adapting comprises restricting the speech recognizer by removing one or more words from an existing vocabulary used for transcription, so as to ensure that the one or more words are not considered by the speech recognizer in producing the second interpretation (Endo et al. col.13, lines 38 – 42; Abrams et al. paragraphs 3, 13 - 20).
As per claim 13, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose adapting comprises restricting the speech recognizer to ensure that in producing the second interpretation, words included in an existing vocabulary are used in particular orders (Endo et al. col.13, lines 38 – 42; Abrams et al. paragraphs 3, 13 - 20).
As per claim 14, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose attributing a meaning to the utterance based on an analysis of the transcription with the second interpretation of the acoustic span replacing the first interpretation of the acoustic span ("The speech-to-text recognizer 30 utilizes word dictionary 34 to attempt to recognize the speech."; Abrams et al., paragraphs 13 - 20).
As per claim 15, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose the speech recognizer performs speech recognition on an entirety of the second copy of the digital representation, including the portion that corresponds to the acoustic span (Abrams et al. paragraphs 13 - 20).
As per claim 16, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose the non-linguistic information is representative of a physical location of the electronic computing device (“other types of information such as the user's home address, habits, preferences, and the like may also be stored in memory in the speech recognition system of the present invention and used to modify the second pass results”; Endo et al., col.13, lines 38 – 42).
As per claim 17, Abrams et al. in view of Griggs et al. and further in view of Endo et al. further disclose the non-linguistic information is representative of a preference or a characteristic of the individual (“other types of information such as the user's home address, habits, preferences, and the like may also be stored in memory in the speech recognition system of the present invention and used to modify the second pass results”; Endo et al., col.13, lines 38 – 42).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Abrams et al. (US PAP 2014/0019126) in view of Griggs et al. (US PAP 2011/0125499); and further in view of Strope et al. (US PAP 2008/0091412).
As per claim 9, Abrams et al. in view of Griggs et al. do not specifically teach
each speech recognizer of the plurality of speech recognizers is designed to process a specific type of proper name.
Strope et al. disclose that there may be multiple speech recognition engines 104 running on different servers situated at different locations, each speech recognition engine 104 accessing one or more databases 106 of language models and being responsible for recognizing specific businesses associated with particular types of businesses and/or geographical locations (paragraph 135).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use plurality of speech recognizers as taught by Strope et al. in Abrams et al. in view of Griggs et al., because that would help improve the accuracy in recognizing the name of the specific business (paragraph 90).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Johnston teaches METHOD FOR ROBUST PERSONALIZATION OF SPEECH RECOGNITION. Okimoto et al. teach personal name recognition.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEONARD SAINT-CYR whose telephone number is (571)272-4247. The examiner can normally be reached Monday- Friday.
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/LEONARD SAINT-CYR/Primary Examiner, Art Unit 2658
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