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 .
DETAILED ACTION
This Office Action corresponds to application 19/311,729 which was filed on 08/27/2025 and claims benefit of EPO 24306458.1 filed 9/5/2024. Claims 1-17 are currently pending.
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.
Step 1
The claims recite a method (claim 1), a system (claim 9), and a non-transitory computer-readable medium (claim 17). These claims fall within at least one of the four categories of patentable subject matter.
Step 2A, Prong One
Claim 1 recites receiving a query, generating a sequence of query hashes for the query, accessing an index, determining temporally matching data from the index, accessing a second index, determining target data, returning results.
The recited steps for querying data, retrieving data, transmitting results are acts of information evaluation and retrieval that can be practically performed in the human mind with the indexes being interepted as generic computer components to apply the instructions of the abstract idea. For example, a person can parse an audio segment and find matches in a list. Thus, these steps are an abstract idea in the “mental processes” grouping.
Dependent claims 2-8 recite additional elements of retrieving data form posting lists, generating a matrix for the query, performing mathematical operations, specifying use of index keys, generating occurrence counts, determining amplitude peaks, and updating the indexes. These are all further extensions of the abstract idea, the additional abstract idea of mathematical concepts, or mere extra-solution activity. For example, with claim 2 a person can generate a matrix and perform calculations; or with claim 4 a person can count occurrences to determine target segments.
Claim 9 recites receiving a query, generating a sequence of query hashes for the query, accessing an index, determining temporally matching data from the index, accessing a second index, determining target data, returning results.
The recited steps for querying data, retrieving data, transmitting results are acts of information evaluation and retrieval that can be practically performed in the human mind with the indexes being interepted as generic computer components to apply the instructions of the abstract idea. For example, a person can parse an audio segment and find matches in a list. Thus, these steps are an abstract idea in the “mental processes” grouping.
Dependent claims 10-16 recite additional elements of retrieving data form posting lists, generating a matrix for the query, performing mathematical operations, specifying use of index keys, generating occurrence counts, determining amplitude peaks, and updating the indexes. These are all further extensions of the abstract idea, the additional abstract idea of mathematical concepts, or mere extra-solution activity. For example, with claim 10 a person can generate a matrix and perform calculations; or with claim 12 a person can count occurrences to determine target segments.
Claim 17 recites receiving a query, generating a sequence of query hashes for the query, accessing an index, determining temporally matching data from the index, accessing a second index, determining target data, returning results.
The recited steps for querying data, retrieving data, transmitting results are acts of information evaluation and retrieval that can be practically performed in the human mind with the indexes being interepted as generic computer components to apply the instructions of the abstract idea. For example, a person can parse an audio segment and find matches in a list. Thus, these steps are an abstract idea in the “mental processes” grouping.
Step 2A, Prong Two
This judicial exception is not integrated into a practical application because the combination of additional elements includes only generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer.
For claims 1-8, the additional elements include the indexes and posting lists.
For claims 9-16, the additional elements include the server, processor, the indexes, and posting lists.
For claims 17, the additional elements include the non-transitory computer-readable storage medium, processor, and the indexes.
The non-transitory computer-readable storage medium, the processor, server, indexes, and posting lists are all recited at a high-level of generality (i.e., as a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Step 2B
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 integration of the abstract idea into a practical application, the additional elements of using the non-transitory computer-readable storage medium, the processor, server, indexes, and posting lists to perform the steps or the additional elements from the dependent claims amounts to no more than part of the abstract idea, mere extra-solution activity, and mere instructions to apply the exception using a generic computer component. The claims are not patent eligible.
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.
Claim(s) 1, 4, 6, 8-9, 12, 14, and 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (“Commercial Mining Based on Temporal Recurrence Hashing Algorithm and Bag-of-Fingerprints Model”, 2011), hereinafter Wu, in view of Cai et al. (US2009/0277322), hereinafter Cai.
Regarding Claim 1:
Wu teaches:
A method of retrieving a target stored audio segment (Wu, section 2.1, note while Wu is focused on video, it uses the same technique for audio streams as well; note fingerprinting technique for audio streams) comprising: receiving a query audio segment (Wu, abstract, section 2.1, note searching for short segments);
generating a sequence of query hashes using the query audio segment, query hashes in the sequence of query hashes being associated with respective temporal positions from the query audio segment (Wu, abstract, section 1-2.2, note hashing frames and searching for reoccurring segments);
accessing a first inverted index using the sequence of query hashes (Wu, section 2.1, note the frames of the stream are mapped to an inverted index via their fingerprints to efficiently search for recurring short segments);
determining a temporally compatible sub-sequence of query hashes in the sequence using data retrieved from the first inverted index, the temporally compatible sub-sequence including query hashes associated with a temporal sequence that matches a temporal sequence of same hashes from at least one stored audio segment (Wu, section 2.1-2.2, note outputting a subset of recurring segment pairs derived from the stream; note the frames of the stream are mapped to an inverted index via their fingerprints to efficiently search for recurring short segments);
accessing a second inverted index using only the temporally compatible sub-sequence (Wu, section 2.2, note the hash functions should be robust so that the pairs derived from the recurring sequences are mapped to the same inverted index);
determining the target stored audio segment based on data retrieved from the second inverted index (Wu, section 1-2.1, note searching for short segments; note the frames of the stream are mapped to an inverted index via their fingerprints to efficiently search for recurring short segments; note mining task aimed at detecting and localizing data in archives); and
transmitting data indicative of the target stored audio segment as a retrieval response to the query audio segment (Wu, section 1-2.2, note searching for short segments, note outputting target segments).
While Wu teaches searching for temporal audio segments, Wu broadly teaches receiving an audio query, to further support this interpretation, Cai is in the same field of endeavor, data management and information retrieval, and Cai teaches:
A method of retrieving a target stored audio segment comprising: receiving a query audio segment (Cai, abstract, figures 1-2, [0017, 0022, 0033, 0040], note audio queries);
generating a sequence of query hashes using the query audio segment, query hashes in the sequence of query hashes being associated with respective temporal positions from the query audio segment (Cai, [0024, 0040, 0046, 0065], note music signature sequences; note queries are constructed using temporal positions of audio);
accessing a first inverted index using the sequence of query hashes (Cai, [0045, 0089], note signatures can be organized by inverted indexes based on hash codes; note using inverted indexes to access data);
determining a temporally compatible sub-sequence of query hashes in the sequence using data retrieved from the first inverted index, the temporally compatible sub-sequence including query hashes associated with a temporal sequence that matches a temporal sequence of same hashes from at least one stored audio segment (Cai, [0026, 0040, 0044-0045, 0066, 0070, 0089], note retrieving data from inverted indexes; note temporal characteristics are determined and used in ranking the results, e.g., determining temporally compatible sub-sequence of query hashes);
accessing a second inverted index using only the temporally compatible sub-sequence (Cai, [0045, 0050, 0089], note signatures are organized by inverted indexes based on hash codes; note inverted indexes hash buckets index similar signatures together, e.g., a second inverted index for temporally compatible sequences);
determining the target stored audio segment based on data retrieved from the second inverted index (Cai, figures 1-2, [0037, 0045, 0089], note retrieving data from the inverted indexes)
transmitting data indicative of the target stored audio segment as a retrieval response to the query audio segment (Cai, figures 1-2, [0037, 0045, 0089], note retrieving data from the inverted indexes; note ranking results; note outputting results).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Cai because all references are directed to data management and information retrieval and because Cai would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and usability of the system by using inverted indexes to organize signatures close to one another (Cai, [0045]).
Regarding Claim 4:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
wherein the determining the target stored audio segment comprises: generating occurrence counts for the candidate stored audio segments (Cai, [0044, 0068-0071], note indexing stage is akin to term extraction for text documents; note determining popular terms, e.g., consider the inverse document frequency (idf) utilized in text retrieval determines occurrence counts for candidates); and
determining the target stored audio segment based on the occurrence counts (Cai, figures 1-2, [0044, 0068-0071], note indexing stage is akin to term extraction for text documents; note determining popular terms, e.g., consider the inverse document frequency (idf) utilized in text retrieval determines occurrence counts for candidates, used in determining results).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Cai because all references are directed to data management and information retrieval and because Cai would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and usability of the system by using inverted indexes to organize signatures close to one another (Cai, [0045]).
Regarding Claim 6:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
periodically updating the first inverted index (Cai, figure 6, [0033, 0080], note a user can update an index, which means a user may periodically update the inverted indexes).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Cai because all references are directed to data management and information retrieval and because Cai would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and usability of the system by using inverted indexes to organize signatures close to one another (Cai, [0045]).
Regarding Claim 8:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
periodically updating the second inverted index (Cai, figure 6, [0045, 0033, 0080], note a user can update an index, which means a user may periodically update the inverted indexes).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Cai because all references are directed to data management and information retrieval and because Cai would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and usability of the system by using inverted indexes to organize signatures close to one another (Cai, [0045]).
Claim 9 discloses substantially the same limitations as claim 1 respectively, except claim 9 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 1 is directed to a method. Therefore claim 9 is rejected under the same rationale set forth for claim 1.
Claim 12 discloses substantially the same limitations as claim 4 respectively, except claim 12 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 4 is directed to a method. Therefore claim 12 is rejected under the same rationale set forth for claim 4.
Claim 14 discloses substantially the same limitations as claim 6 respectively, except claim 14 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 6 is directed to a method. Therefore claim 14 is rejected under the same rationale set forth for claim 6.
Claim 16 discloses substantially the same limitations as claim 8 respectively, except claim 16 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 8 is directed to a method. Therefore claim 16 is rejected under the same rationale set forth for claim 8.
Claim 17 discloses substantially the same limitations as claim 1 respectively, except claim 17 is directed to a non-transitory computer readable medium comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 1 is directed to a method. Therefore claim 17 is rejected under the same rationale set forth for claim 1.
Claim Rejections - 35 USC § 103
Claim(s) 2, 7, 10, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Cai, Ustimenko (US2021/0319359), and Bryan et al. (US2023/0129350), hereinafter Bryan.
Regarding Claim 2:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
wherein the determining the temporally compatible sub-sequence comprises: generating a digital matrix based on the sequence and the data retrieved from the first inverted index (Wu, section 2.1-2.2, note outputting a subset of recurring segment pairs derived from the stream; note the frames of the stream are mapped to an inverted index via their fingerprints to efficiently search for recurring short segments) (Cai, [0026, 0040, 0044-0045, 0066, 0070, 0089], note retrieving data from inverted indexes; note temporal characteristics are determined and used in ranking the results, e.g., determining temporally compatible sub-sequence of query hashes;),
determining a diagonal value for a given diagonal in the digital matrix (Wu, sections 2.1-2.2, note using mathematics and statistics to determine temporal compatibility) (Cai, figure 1, [0026, 0029, 0040, 0044-0045, 0049, 0070, 0089], note retrieving data from inverted indexes; note determining temporal characteristics; note dimensional vectors are calculated to characterize temporal variation used for sequence of signatures; note mathematical and statistical analysis of audio segments for determining temporal compatibility); and
determining the temporally compatible sub-sequence using the given diagonal (Wu, sections 2.1-2.2, note using mathematics and statistics to determine temporal compatibility) (Cai, figure 1, [0026, 0029, 0040, 0044-0045, 0049, 0070, 0089], note retrieving data from inverted indexes; note determining temporal characteristics; note dimensional vectors are calculated to characterize temporal variation used for sequence of signatures; note mathematical and statistical analysis of audio segments for determining temporal compatibility).
While Wu as modified teaches searching for temporal audio segments using inverted indexes, Wu as modified doesn’t specifically mention posting lists; However, Ustimenko is the same field of endeavor, data management and information retrieval, and Ustimenko teaches:
generating a digital matrix based on the sequence and the data retrieved from the first inverted index (Ustimenko, [0081-0085], note each inverted index comprises posting lists; note this may be for sound-based queries. When combined with the previously cited references this would be for the inverted index for audio segments as taught by Wu and Cai)
the data retrieved from the first inverted index including a first posting list associated with a corresponding query hash from the sequence (Ustimenko, [0081-0085], note each inverted index comprises posting lists; note this may be for sound-based queries. When combined with the previously cited references this would be for the inverted index for audio segments as taught by Wu and Cai)
the first posting list being indicative of whether the corresponding query hash is present at a given temporal position in at least one stored audio segment (Ustimenko, [0081-0085], note each inverted index comprises posting lists; note this may be for sound-based queries. When combined with the previously cited references, this would be for the inverted index for audio segments as taught by Wu and Cai);
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Ustimenko because all references are directed to data management and information retrieval and because Ustimenko would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and efficiency of the system by using posting lists for retrieving results.
While Wu as modified broadly teaches mathematical and statical calculations on the audio segments to determine temporal compatibility; Bryan is the same field of endeavor, data management and information retrieval, and Bryan teaches:
determining a diagonal value for a given diagonal in the digital matrix (Bryan, abstract, [0032, 0051, 0055], note matrix analysis/calculations of audio embeddings for temporal compatibility, which is interpreted to include diagonal values. When combined with the previously cited references this would be for the data retrieved from the inverted indexes as taught by Wu, Cai, and Ustimenko); and
determining the temporally compatible sub-sequence using the given diagonal (Bryan, abstract, [0032, 0051, 0055], note matrix analysis/calculations of audio embeddings for temporal compatibility, which is interpreted to include diagonal values. When combined with the previously cited references this would be for the data retrieved from the inverted indexes as taught by Wu, Cai, and Ustimenko).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Bryan because all references are directed to data management and information retrieval and because Bryan would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and efficiency of the system by using various analysis techniques such as nearest neighbor analysis.
Regarding Claim 7:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
the digital matrix is generated for the query audio segment (Wu, section 2.1-2.2, note outputting a subset of recurring segment pairs derived from the stream; note the frames of the stream are mapped to an inverted index via their fingerprints to efficiently search for recurring short segments) (Cai, [0026, 0040, 0044-0045, 0049, 0066, 0070, 0089], note retrieving data from inverted indexes; note temporal characteristics are determined and used in ranking the results, e.g., determining temporally compatible sub-sequence of query hashes).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Cai because all references are directed to data management and information retrieval and because Cai would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and usability of the system by using inverted indexes to organize signatures close to one another (Cai, [0045]).
Claim 10 discloses substantially the same limitations as claim 2 respectively, except claim 10 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 2 is directed to a method. Therefore claim 10 is rejected under the same rationale set forth for claim 2.
Claim 15 discloses substantially the same limitations as claim 7 respectively, except claim 15 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 7 is directed to a method. Therefore claim 15 is rejected under the same rationale set forth for claim 7.
Claim Rejections - 35 USC § 103
Claim(s) 3 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Cai and Ustimenko.
Regarding Claim 3:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
wherein the accessing the second inverted index comprises: using hash-position pairs from the temporally compatible sub-sequence as index keys for identifying a second posting list, the second posting list being indicative of candidate stored audio segments (Wu, abstract, sections 1-2.2, note searching for short segments) (Cai, [0024, 0040, 0045, 0089], note indexing based on hash codes; note hashing is applied to index signatures for parameters for indexing. When combined with Ustimenko this would be for identifying the posting lists indicative of candidate audio results).
While Wu as modified teaches searching for temporal audio segments using inverted indexes, Wu as modified doesn’t specifically mention posting lists; However, Ustimenko is the same field of endeavor, data management and information retrieval, and Ustimenko teaches:
wherein the accessing the second inverted index comprises: using hash-position pairs from the temporally compatible sub-sequence as index keys for identifying a second posting list, the second posting list being indicative of candidate stored audio segments (Ustimenko, [0081-0085], note each inverted index comprises posting lists; note this may be for sound-based queries; note the posting lists are for the index keys and are indicative of candidate results. When combined with the previously cited references, this would be for the inverted index for audio segments as taught by Wu and Cai);
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Ustimenko because all references are directed to data management and information retrieval and because Ustimenko would expand upon the teachings of the previously cited references in information retrieval which would improve the performance and efficiency of the system by using posting lists for retrieving results.
Claim 11 discloses substantially the same limitations as claim 3 respectively, except claim 11 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 3 is directed to a method. Therefore claim 11 is rejected under the same rationale set forth for claim 3.
Claim Rejections - 35 USC § 103
Claim(s) 5 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Cai and Kleijn et al. (US2015/0248893), hereinafter Kleijn.
Regarding Claim 5:
Wu as modified shows the method as disclosed above;
Wu as modified further teaches:
wherein the generating the sequence (Wu, abstract, section 1-2.2, note hashing frames and searching for reoccurring segments) (Cai, [0024, 0040, 0046, 0065], note music signature sequences; note queries are constructed using temporal positions of audio);
generating, using a hashing function, the sequence based on the sequence of groups (Wu, abstract, section 1-2.2, note hashing frames and searching for reoccurring segments) (Cai, [0024, 0040, 0046, 0065], note music signature sequences; note queries are constructed using temporal positions of audio).
While Wu as modified teaches searching for temporal audio segments using inverted indexes, Wu as modified doesn’t specifically teach using amplitude peaks; However, Kleijn is the same field of endeavor, data analysis and information retrieval, and Kleijn teaches:
determining amplitude peaks for the given audio segment (Kleijn, [0004], note determining amplitude peaks for an audio segment);
determining a sequence of groups of peaks using the amplitude peaks (Kleijn, [0004], note determining amplitude peaks for an audio segment and ordering the determined peaks, e.g., sequencing); and
generating, using a hashing function, the sequence based on the sequence of groups of peaks (Kleijn, [0004], note determining amplitude peaks for an audio segment and ordering the determined peaks, e.g., sequencing. When combined with the previously cited references this would be for the sequencing as taught by Wu and Cai).
It would have been obvious to one of ordinary skill in the art before the effective date of filing to modify the cited references to incorporate the teachings of Kleijn because all references are directed to data analysis and information retrieval and because Kleijn would expand upon the teachings of the previously cited references in data analysis which would improve the performance and accuracy of the system by using audio characteristics to determine target data.
Claim 13 discloses substantially the same limitations as claim 5 respectively, except claim 13 is directed to a system comprising a server comprising a processor (Cai, figure 7, note computing device and processing unit) while claim 5 is directed to a method. Therefore claim 13 is rejected under the same rationale set forth for claim 5.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Li et al. (US11182426) teaches audio retrieval;
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/JOHN J MORRIS/Examiner, Art Unit 2151 6/22/2026
/James Trujillo/Supervisory Patent Examiner, Art Unit 2151
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