DETAILED ACTION
Claims 1-20 are pending.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant’s submission filed on 02 February 2026 has been entered.
Response to Amendment
With regard to the Final Office Action from 31 October 2025, the Applicant has filed a response on 02 February 2026.
Response to Arguments
With regard to the 35 U.S.C. 101 rejection given particularly to independent claims 1 and 12 for being directed to a judicial exception without significantly more, the Applicant reminds (Remarks: page 11 par 1) the Examiner of what it means for a claim to recite a mathematical concept based on the ‘October Update’ to indicate that the recitation of a mathematical concept to include mathematical relationships, formulas or equations and calculations, rather than claim limitations that are only based on or involves a mathematical concept. To this, the Examiner refers to the recited generation of a vector representation, the calculated cosine similarity, the Levenshtein distance, all of which are clear mathematical computations which can only be performed as mathematical calculations and not just as the inclusion of mathematical concepts. The Applicant then mentions (Remarks: page 11 par 2) that claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, further stating that this is the case with the limitations of these independent claims. The Applicant has amended the independent claims to include the recitation of a pointwise mutual information, stating that this is ‘… utilized for natural language processing in machine learning and is not suitable for use by a human.’ While the Examiner agrees that this is used in a machine learning environment and a human wouldn’t necessarily carry out the identification of word collocations through a PMI, the Examiner indicates regarding this amendment, that, a PMI by itself is a mathematical concept, and in fact, a mathematical calculation. The Applicant has further amended the claims (Remarks: page 12 par 1) to indicate that the operations are performed by a computing system. To this, the Examiner indicates that mentioning the performance by a computing system simply introduces a device being used to perform the judicial exceptions, but its presence does not amount to the claim being significantly more than the mentioned judicial exception. A generic computer, or a generic processor can take the position of this computing system here, thereby showing that it is not particularly an additional element having its presence overcome the judicial exception rejection.
The Applicant mentions (Remarks: page 12 par 2) that the ‘claims, when considered as a whole, has clearly been integrated into a practical application of an abstract idea regardless of the characterization of that abstract idea …’ but fails to mention the particular practical application that is being integrated here.
The Applicant indicates (Remarks: page 13 par 3) that ‘the claim features are recited with specificity and impose meaningful limits’ such as the details ‘pertaining to how alternative text suggestions are generated … including determining pointwise mutual information to identify word collocations …’ The Examiner indicates to this that the identification of alternative text suggestions is itself a mental process that can be performed by a human, with the use of a PMI as the applied method, which the Examiner also already indicated to be a mathematical computation by itself. The further replacing of ‘a space between words in each collocation with a character determined not to be a candidate for transcription’ is also purely a mental process which can be performed by a human while writing the word down to indicate to others reading it that it was determined as a bi-gram, but represented as a unigram with a symbol between the two words that make up the bi-gram.
Regarding the consideration of if the additional elements integrate the judicial exception into a practical application, the Applicant indicates (Remarks: page 14 par 4) that the Specification clearly sets out a technical problem and a corresponding technical improvement in the field of machine-based automated speech recognition. While this may be true for the invention as a whole, the Applicant’s remark does not yet make it clear as to what part of the claims is to be considered as the applicable additional elements that are being integrated. As will further be seen by the Examiner’s prior art rejection, the tasks being performed by the claims are not entirely novel to the point of being considered an improvement to the applicable technical field, and thereby suitable to demonstrate an integration into a practical application.
The Applicant addresses (Remarks: page 15 par 3 – page 16 par 4) to indicate that regardless of the Examiner’s indication of the claims’ classification as an alleged abstract idea, the claimed features are ‘not taught by the prior art of record’ and the claims include additional features that are not well-understood, routine, or conventional in the art, to indicate that the claims constitute significantly more than an abstract idea. The Examiner mentioned earlier, to this note, that the claims will be addressed using prior art in the prior art rejection section of this Office Action.
The Examiner hereby maintains the 35 U.S.C. 101 rejection.
Regarding the prior art rejection, the Applicant arguments have been considered, but are moot in light of the new ground of rejection necessitated by the amendment to the claims. The claim will be addressed by their current presentation in the following section.
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 a judicial exception without significantly more.
Independent claims 1 and 12 recite the limitations of generating automatic alternative text suggestions for a speech recognition engine of a contact centre system by identifying at least one word collocation in text corpus through the use of pointwise mutual information, replacing each word collocation with a respective unigram by replacing the space between the words with a character determined not to be a candidate for transcription, generating a vector representation of each unique word in a contact centre communication text corpus through applying word embedding, calculating a cosine similarity between each vector representation and each other vector representation, generating a filtered set of word pairs based on the cosine similarity and a threshold, calculating a Levenshtein distance between words of each word pair of the first set of word pairs that have been filtered through the earlier cosine similarity results, and generating a candidate list of alternative words for a target word based on the calculated Levenshtein distance.
Nothing mentioned in the claims preclude them from being performed as a mathematical concept and in the human mind. The entire process involves making a determination to obtain and edit certain words, performing certain calculations and then making a decision that can be performed by human judgement. It involves data gathering to identify word collocations from a text corpus, which a human may identify by sight, and as provided here, the use of a pointwise mutual information is a mathematical concept applied to identifying the word collocations, data transformation to replace a word collocation with a modified unigram which a human may perform through the use of pen and paper, data transformation through the mathematical computation of applying a word embedding model to generate a vector representation of each unique available word, the mathematical process of computing a cosine similarity of each vector in relation to each other computer vector, the mental decision to discard word pairs with cosine similarity results determined to be below a threshold, the mathematical computation of calculating a Levenshtein distance between words of each word pair that hasn’t been discarded, and then the final mental decision of generating a candidate list of alternative words for a target word based on the Levenshtein distance between words of each of the available word pairs. The claims hereby recite a mathematical concept and a mental process.
This judicial exception is not integrated into a practical application as the claims simply teach of gathering data, transforming data by replacing spaces in word collocations and transforming from word form into vector form, performing calculations, making analyses and decisions based on the calculations and presenting the final available data. While the claims do mention a computing system comprising a processor and a memory, these are recited in generic terms.
The invention is not tied to any particular defining structure and simply provides instructions to apply the judicial exception. The technique can be performed by a generic computer which would be presented as a tool to implement the abstract idea (classifiable as automation of the mental process steps). The Specification in [0068] provides a generic computer as one or more computing devices for performing the various functionalities that are required of the claimed system, this being suitable to read upon the limitations of these claims. This is recited at a high level of generality that it amounts to no more than mere instructions to apply the exception using a generic computer. The claims do not provide any additional detail. The claims therefore do not include additional elements that would be sufficient to amount to significantly more than the judicial exception because the invention is not tied to a practical application.
The claims provide techniques that amount to no more than mere instructions that apply the judicial exception which can be performed by a generic device. Merely mentioning the computing system, processor and memory amounts to no more than general-purpose hardware used as tools to implement the abstract idea and does not provide any particular application other than applying it for the purpose of implementing a judicial exception. Mere instructions to apply an exception using a generic device cannot provide an inventive concept. Claims 1 and 12 are not eligible.
Claim 2 provides that word embedding model comprises a word2vec model. The presence of a word2vec model simply serves as the mathematical tool applied to performing the word embedding. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 3 provides applying the word embedding model is in response to identifying the at least one word collocation in the text corpus and replacing each word collocation of the at least one word collocation in the text corpus with the respective modified unigram. A human may identify and replace a word collocation in the text corpus with a respective unigram. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 4 provides that in generating the candidate list of alternative words for the target word, each modified unigram is replaced with a respective original word collocation. This can be performed as a mental task whereby a human makes a replacement of a modified unigram with a word collocation. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 5 provides sorting the candidate list of alternative words, displaying the sorted candidate list to the user, and receiving the user’s selection of alternative words. This indicates a mental process that can be performed by a user for having the user sort alternative words, displaying them, and making manual replacements. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 6 provides the automatic selection of one or more alternative words from a candidate list as alternative text for the target word based the Levenshtein distance computation. A human may make a selection of alternative words as well while making use of a computed distance metric. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 7 provides determining a number of occurrences in the text corpus of each word of the filtered set of word pairs. A human may count the number of times an occurrence is encountered. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 8 provides generating the candidate list of alternative words, based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs and the number of occurrences in the text corpus of each word of the filtered set of words. This indicates the mental process of following certain conditions for the purpose of accepting certain words as the generated candidate list of alternative words. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 9 provides the automatic generation of a plurality of transcripts in the text corpus making use of greedy decoding. Generating a transcript is a task that can be performed by a human, and the use of greedy decoding simply involves selecting the option with the highest probability which a human can perform. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 10 provides the automatic generation of a plurality of transcripts using prefix-beam decoding. Generating a transcript is a task that can be performed by a human, and the use of prefix-beam decoding is a well-known search algorithm applied to speech recognition. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 11 provides the generation of the candidate list of alternative words for the target word in response to receiving a user request for alternative words for the target word. This involves human input for the alternative words. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 13 provides that word embedding model comprises a word2vec model. The presence of a word2vec model simply serves as the mathematical tool applied to performing the word embedding. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 14 provides applying the word embedding model is in response to identifying the at least one word collocation in the text corpus and replacing each word collocation of the at least one word collocation in the text corpus with the respective modified unigram. A human may identify and replace aa word collocation in the text corpus with a respective unigram. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 15 provides that in generating the candidate list of alternative words for the target word, each modified unigram is replaced with a respective original word collocation. This can be performed as a mental task whereby a human makes a replacement of a modified unigram with a word collocation. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 16 provides sorting the candidate list of alternative words, displaying the sorted candidate list to the user, and receiving the user’s selection of alternative words. This indicates a mental process that can be performed by a user for having the user sort alternative words, displaying them, and making manual replacements. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 17 provides the automatic selection of one or more alternative words from a candidate list as alternative text for the target word based the Levenshtein distance computation. A human may make a selection of alternative words as well while making use of a computed distance metric. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 18 provides determining a number of occurrences in the text corpus of each word of the filtered set of word pairs. A human may count the number of times an occurrence is encountered. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 19 provides generating the candidate list of alternative words, based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs and the number of occurrences in the text corpus of each word of the filtered set of words. This indicates the mental process of following certain conditions for the purpose of accepting certain words as the generated candidate list of alternative words. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
Claim 20 provides the automatic generation of a plurality of transcripts in the text corpus making use of greedy decoding. Generating a transcript is a task that can be performed by a human, and the use of greedy decoding simply involves selecting the option with the highest probability which a human can perform. This does not integrate any practical application nor does it provide any additional element sufficient to amount to more than the mentioned judicial exception.
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.
Claims 1, 2, 3, 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Kwatra et al. (US 2022/0172713 A1: hereafter — Kwatra) in view of Lev et al. (US 2017/0018269 A1: hereafter — Lev) further in view of Molony et al. (US 2022/0093255 A1: hereafter — Molony), further in view of Fauber (US 2021/0232616 A1), further in view of Ehlen et al. (US 2015/0186790 A1: hereafter — Ehlen) and further in view of SHISHIDO et al. (US 2022/0197962 A1: hereafter — Shishido).
For claim 1, Kwatra discloses:
applying, by the computing system, a word embedding model to generate a vector representation of each unique word in a contact center communication text corpus (Kwatra: [0003] — obtaining a textual rendering of an audio portion of a video; [0023] — mapping words into vectors while making use of vector embedding);
calculating, by the computing system, a cosine similarity of each vector representation and each other vector representation generated by the word embedding model (Kwatra: [0035] — applying a cosine similarity to obtain the similarity between vector representations of two words);
calculating, by the computing system, a Levenshtein distance between words of each word pair of the filtered set of word pairs [[generated from discarding word pairs that are determined to have cosine similarity results that fall below the predefined threshold]] (Kwatra: [0037] — computing the Levenshtein distances of a word relative to other words that are contained in a textual rendering of an audio portion); and
generating, by the computing system, a candidate list of alternative words for a target word based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs (Kwatra: [0037]-[0038] — the Levenshtein distances is applied to determining a certain number of words that are semantically close to similar to particular word for the words in a vocabulary; FIG. 2 Step 208 — selecting from among a multi-word vocabulary, a plurality of candidate words for replacing mistranscriptions (teaching the generation of a candidate list)).
The reference of Kwatra fails to disclose the limitation regarding the generation of alternative text suggestion for a speech recognition engine of a contact center, but this is instead seen to be taught by the reference of Lev as:
a method for generating automatic alternative text suggestions for a speech recognition engine of a contact center system (Lev: [0011] — in a contact center environment, performing speech recognition and automatically providing suggestions to recognised utterances).
The reference of Kwatra provides teaching for obtaining semantically related words to a target word, but differs from the claimed invention in that the claimed invention further provides that automatic generation of alternative text suggestions in a contact centre environment. This isn’t new to the art as the reference of Lev is seen to teach above.
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Lev which provides the automatic suggesting of words encountered in a contact centre environment, with the teaching of Kwatra which provides teaching for the obtaining of semantically related words, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of applying the collection of semantically related words to a target word, in a situation that requires a lot of dialoguing such as a contact centre, whereby the presence of replacement words to some current words could aid in improving a conversation. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
The combination Kwatra in view of Lev fails to teach the further limitation of this claim, for which the reference of Molony is now introduced to teach as:
discarding, by the computing system, each calculated cosine similarity result determined to be below a predefined threshold to generate a filtered set of word pairs (Molony: [0103] — obtaining a cosine similarity between two vectors and discarding terms for which the cosine distance between them is greater than a threshold (so discarding terms for which the cosine similarity is less than a threshold)).
The combination of Kwatra in view of Lev provides teaching for obtaining a cosine similarity of vectors representing words. It differs from the claimed invention in that the claimed invention further provides teaching for discarding each calculated cosine similarity with values below a threshold. This isn’t new to the art as the reference of Molony is seen to teach above.
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Molony which allows or discards comparisons based on calculated cosine similarities, to improve upon the teaching of the combination of Kwatra in view of Lev which simply determines similarities between words based on a calculated cosine similarity, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of setting limits for the relationship to be obtained so that dissimilar words may not be tied together. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
The combination of Kwatra in view of Lev further in view of Molony provides teaching for calculating a Levenshtein distance between words of each word pair of a filtered set of word pairs. It however fails to teach that the Levenshtein distance particularly if generated from discarding word pairs that have been determined to fall within a threshold range.
The reference of Fauber is however introduced to teach this as:
calculating, by the computing system, a Levenshtein distance between words of each word pair of the filtered set of word pairs generated from discarding word pairs that are determined to have cosine similarity results that fall below the predefined threshold (Fauber: FIG. 4A, [0060] — a list of strings is obtained as an input and for the obtained list of strings (consider the obtained list of strings as a filtered set of words), an edit distance is computed for pairs in the string using a Levenshtein distance to obtain similarity (noting that the Molony reference in [0103] has been shown to teach of discarding terms for which the cosine similarity is less than a threshold, thereby teaching of performing a Levenshtein distance on words of a filtered word set)).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Fauber which applies a Levenshtein distance to measure the similarity between words of filtered word set, with the teaching of the combination of Kwatra in view of Lev further in view of Molony which teaches that a cosine similarity is applied to obtain a filtered word set, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of generating further similarities between words that are already contained within a cosine-similarity-filtered word set, thereby enhancing the similarity between words. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
The combination of Kwatra in view of Lev further in view of Molony and further in view of Fauber provides teaching for generating a candidate list of alternative words for target words in a contact centre environment, but differs from the claimed invention in that the claimed invention now further provides teaching for applying pointwise mutual information to identify at least one word collocation in a text corpus. This is however not new to the art as the reference of Ehlen is now seen to teach this as:
determining, by a computing system, pointwise mutual information to identify at least one word collocation in a contact center communication text corpus (Ehlen: [0040] — using pointwise mutual information to identify multiple word expressions, such as bigrams).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found the incorporation of the known pointwise mutual information technique as taught by Ehlen, to improve upon the candidate list of alternative words generation as taught by the combination of Kwatra in view of Lev further in view of Molony and further in view of Fauber, as an obvious method to try for the purpose of obtaining word collocations. The combination of both prior art elements would have provided the predictable result of an easily applicable technique able to recognise bi-grams, so that alternative spellings of the bi-grams may be generated. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
The combination of Kwatra in view of Lev, further in view of Molony, further in view of Fauber and further in view of Ehlen provides teaching for identifying word collocations in a contact centre environment, but differs from the claimed invention in that the claimed invention now further provides teaching for replacing the space between each word collocation with a character that is not a candidate for transcription. This is however not new to the art as the reference of Shishido is now seen to teach this as:
replacing, by the computing system, each word collocation of the at least one word-collocation in the text corpus with a respective modified unigram by replacing a space between words in the collocation with a character determined not to be a candidate for transcription (Shishido: [0049] — transforming n-gram tokens (taken here as bi-gram word collocations) into single word tokens where the white spaces are replaced with a special character such as an underscore (an underscore being a character that wouldn’t be a candidate for transcription)).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Shishido which replaces whitespaces in a word collocation with an underscore special character, into the teaching of the combination of Kwatra in view of Lev, further in view of Molony, further in view of Fauber and further in view of Ehlen which provides identifying the word collocations, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of simply performing text normalisation to present certain words in a certain desirable form. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
For claim 2, claim 1 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido discloses the method, wherein the word embedding model comprises a word2vec model (Molony: [0088] — generating embedding vectors using Word2Vec).
For claim 3, claim 1 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido discloses the method
wherein applying the word embedding model comprises applying the word embedding model in response to identifying the at least one word collocation in the text corpus and replacing each word collocation of the at least one word collocation in the text corpus with the respective modified unigram (Shishido: [0048]–[0049] — performing word embedding, replacing a white space with a special character to obtain a single word token).
As for claim 12, system claim 12 and method claim 1 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Kwatra in [0004] provides a processor, and in [0021], provides a storage memory suitable to read upon the limitations of this claim. Accordingly, claim 12 is similarly rejected under the same rationale as applied above with respect to method claim 1.
As for claim 13, system claim 13 and method claim 2 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 13 is similarly rejected under the same rationale as applied above with respect to method claim 2.
As for claim 14, system claim 14 and method claim 3 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 14 is similarly rejected under the same rationale as applied above with respect to method claim 3.
Claims 5, 6, 7, 8, 16, 17, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Kwatra (US 2022/0172713 A1) in view of Lev (US 2017/0018269 A1) further in view of Molony (US 2022/0093255 A1), further in view of Fauber (US 2021/0232616 A1), further in view of Ehlen (US 2015/0186790 A1) and further in view of Shishido (US 2022/0197962 A1) as applied to claim 1, and further in view of Koceinda et al. (US 2009/0174667 A1: hereafter — Kocienda).
For claim 5, claim 1 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido provides teaching for performing speech recognition in a contact centre environment as provided by the final limitation of this claim (Lev: [0011] — performing speech recognition in a contact centre environment). This combination however differs from the claimed invention in that the claimed invention further teaches the further limitations of this claim, which the reference of Kocienda is now introduced to teach as:
the method, further comprising:
sorting the candidate list of alternative words for the target word based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs (Kocienda: [0085] — performing scoring based on Levenshtein distance such that the candidate words are selected for presentation based on their edit distance scores);
displaying the sorted candidate list to the user (Kocienda: [0085] — candidate words are selected for presentation; [0091] — display of the words); and
receiving the user’s selection of one or more alternative words from the candidate list to be used as alternative text for the target word in the [[speech recognition engine of the contact center system]] (Kocienda: [0091]–[0092] — presentation for selection by the user).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Kocienda which ranks candidate words according to a calculated Levenshtein distance to have the user make a selection from the displayed candidate words, to improve upon the teaching of the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido which simply calculates a Levenshtein distance to determine alternative words, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of granting a user control over which of the alternate words should be used. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
For claim 6, claim 1 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido provides teaching for performing speech recognition in a contact centre environment as provided by this claim (Lev: [0011] — performing speech recognition in a contact centre environment). This combination however differs from the claimed invention in that the claimed invention further teaches the further limitations of this claim, which the reference of Kocienda is now introduced to teach as:
the method, further comprising automatically selecting, based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs, one or more alternative words from the candidate list as alternative text for the target word in the speech recognition engine of the contact center system (Kocienda: [0156], FIG. 11A Parts 644, 645 — the automatic selection of an alternate word — dinner which is similar to the currently-typed word; [0085] — performing scoring based on Levenshtein distance).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Kocienda which provides a system that automatically selects a one or more alternative words based on a Levenshtein distance between words, to improve upon the teaching of the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido which simply calculates a Levenshtein distance to determine alternative words, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of presenting a system that makes it easier for a user to quickly accept an alternate word selection without having to bother about making the personal selection decision. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
For claim 7, claim 1 is incorporated and as applied to claim 5 above, the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, further in view of Shishido, and further in view of Kocienda provides the method, further comprising determining a number of occurrences in the text corpus of each word of the filtered set of word pairs (Kocienda: [0085] — considering usage frequency of words).
For claim 8, claim 7 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, further in view of Shishido, and further in view of Kocienda discloses the method, wherein generating the candidate list of alternative words for the target word comprises generating the candidate list of alternative words for the target word based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs and the number of occurrences in the text corpus of each word of the filtered set of words (Kocienda: [0085] — performing scoring based on Levenshtein distance as well as usage frequency ranking).
As for claim 16, system claim 16 and method claim 5 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 16 is similarly rejected under the same rationale as applied above with respect to method claim 5.
As for claim 17, system claim 17 and method claim 6 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 17 is similarly rejected under the same rationale as applied above with respect to method claim 6.
As for claim 18, system claim 18 and method claim 7 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 18 is similarly rejected under the same rationale as applied above with respect to method claim 7.
As for claim 19, system claim 19 and method claim 8 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 19 is similarly rejected under the same rationale as applied above with respect to method claim 8.
Claims 9 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kwatra (US 2022/0172713 A1) in view of Lev (US 2017/0018269 A1) further in view of Molony (US 2022/0093255 A1), further in view of Fauber (US 2021/0232616 A1), further in view of Ehlen (US 2015/0186790 A1) and further in view of Shishido (US 2022/0197962 A1) as applied to claim 1, and further in view of LI et al. (US 2020/0335082 A1: hereafter — Li).
For claim 9, claim 1 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido provides teaching for performing speech recognition in a contact centre environment as provided by this claim (Lev: [0011] — performing speech recognition in a contact centre environment). This combination however differs from the claimed invention in that the claimed invention further teaches the further limitations of this claim, which the reference of Li is now introduced to teach as:
the method, further comprising automatically generating a plurality of transcripts of the contact center communication text corpus using greedy decoding (Li: [0073] — using greedy decoding to generate an automatic speech recognition decoding hypothesis).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Li which applies a greedy decoding algorithm for generating a plurality of transcripts, with the teaching of the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido which teaches of performing speech recognition at a contact centre environment, thereby coming up with the claimed invention, as an obvious method to try. The combination of both prior art elements would have provided the predictable result of choosing the highest probable transcript as the textual translation of an input speech. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
As for claim 20, system claim 20 and method claim 9 are related as system and the method of using same, with each claimed element’s function corresponding to the claimed method step. Accordingly, claim 20 is similarly rejected under the same rationale as applied above with respect to method claim 9.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Kwatra (US 2022/0172713 A1) in view of Lev (US 2017/0018269 A1) further in view of Molony (US 2022/0093255 A1), further in view of Fauber (US 2021/0232616 A1), further in view of Ehlen (US 2015/0186790 A1) and further in view of Shishido (US 2022/0197962 A1) as applied to claim 1, and further in view of Moritz et al. (US 2021/0183373 A1: hereafter — Moritz).
For claim 10, claim 1 is incorporated and the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido provides teaching for performing speech recognition in a contact centre environment as provided by this claim (Lev: [0011] — performing speech recognition in a contact centre environment). This combination however differs from the claimed invention in that the claimed invention further teaches the further limitations of this claim, which the reference of Moritz is now introduced to teach as:
the method, further comprising automatically generating a plurality of transcripts of the contact center communication text corpus using prefix-beam decoding (Moritz: [0129] — prefix beam search module for outputting transcriptions).
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Moritz which applies a prefix beam searching algorithm for generating a plurality of transcripts, with the teaching of the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido which teaches of performing speech recognition at a contact centre environment, thereby coming up with the claimed invention, as an obvious method to try. The combination of both prior art elements would have provided the predictable result of incorporating the use of a language model to aid in the decoding process of speech recognition as applied by a prefix-beam decoding, resulting in more educated decisions for speech recognition. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Kwatra (US 2022/0172713 A1) in view of Lev (US 2017/0018269 A1) further in view of Molony (US 2022/0093255 A1), further in view of Fauber (US 2021/0232616 A1), further in view of Ehlen (US 2015/0186790 A1) and further in view of Shishido (US 2022/0197962 A1) as applied to claim 1, and further in view of Williamson et al. (US 2005/0096914 A1: hereafter — Williamson).
For claim 11, claim 1 is incorporated but the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido fails to disclose the limitation of this claim, for which the reference of Williamson is now introduced to teach as the method, wherein generating the candidate list of alternative words for the target word comprises generating the candidate list of alternative words for the target word in response to receiving a user request for alternative words for the target word (Williamson: [0037] — the user may then request alternates for the converted words for the alternate words to then get presented).
The combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido provides teaching for the presenting of alternative words for a target word. This however differs from the claimed invention in that the claimed invention further provides teaching for having the user make a request for the presentation of the alternative words. This isn’t new to the art as the reference of Williamson is seen to teach above.
Hence, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to incorporate the known technique of Williamson which allows a user make a request for the presentation of the alternative words, to be combined with the presence of the alternative words as provided by the combination of Kwatra in view of Lev further in view of Molony, further in view of Fauber, further in view of Ehlen, and further in view of Shishido, to thereby come up with the claimed invention. The combination of both prior art elements would have provided the predictable result of ensuring that the user receives alternate word suggestion sonly when the user desires such. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
Potentially Allowable Subject Matter
Claims 4 and 15 would be objected to for being dependent on a rejected base claim, and would potentially be allowable if rewritten to overcome the rejection under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of their base claims and any intervening claims.
With regard to claims 4 and 15, the prior art of record taken alone or in
combination fail to teach, inter alia, the generating of the candidate list of alternative words for the target word comprises replacing each modified unigram with a respective original word collocation.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure. See PTO-892.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to OLUWADAMILOLA M. OGUNBIYI whose telephone number is (571)272-4708. The Examiner can normally be reached Monday – Thursday (8:00 AM – 5:30 PM Eastern Standard Time).
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If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s Supervisor, PARAS D. SHAH can be reached at (571) 270-1650. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/OLUWADAMILOLA M OGUNBIYI/Examiner, Art Unit 2653
/Paras D Shah/Supervisory Patent Examiner, Art Unit 2653
02/22/2026