Prosecution Insights
Last updated: July 17, 2026
Application No. 19/085,949

AUDIO STEM IDENTIFICATION SYSTEMS AND METHODS

Final Rejection §DP
Filed
Mar 20, 2025
Priority
Sep 19, 2019 — continuation of 10/997,986 +2 more
Examiner
LE, HUNG D
Art Unit
2161
Tech Center
2100 — Computer Architecture & Software
Assignee
Spotify AB
OA Round
2 (Final)
90%
Grant Probability
Favorable
3-4
OA Rounds
1y 0m
Est. Remaining
96%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allowance Rate
980 granted / 1087 resolved
+35.2% vs TC avg
Moderate +6% lift
Without
With
+6.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
18 currently pending
Career history
1113
Total Applications
across all art units

Statute-Specific Performance

§101
5.2%
-34.8% vs TC avg
§103
61.5%
+21.5% vs TC avg
§102
14.6%
-25.4% vs TC avg
§112
7.2%
-32.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1087 resolved cases

Office Action

§DP
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 1. This Office Action is in response to the amendment filed on 05/04/2026. Claims 1-2, 8-10 and 16-18 have been amended. Claims 1-20 are pending. Information Disclosure Statement 2. The information disclosure statement (IDS) filed on 02/04/2026 complies with the provisions of M.P.E.P. 609. The examiner has considered it. Response to Arguments 3. This office action has been issued in response to amendment filed 05/04/2026. Claims 1-1-20 are pending. Applicants’ arguments have been carefully and respectfully considered in light of the instant amendment as they relate to the claim rejections under double patenting as will be discussed below. Accordingly, this action has been made final. Double Patenting 4. 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" ranted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type 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 Omum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and 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 a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b). 5. Claims 1-20 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 12,283,287. Although the conflicting claims are not identical, they are not patentably distinct from each other. Instant Application 19085949 Patent US 12,283,287 Claim 1: A computer system, comprising: at least one processor; and at least one memory storing instructions which when executed by the at least one processor cause the at least one processor to: receive a query corresponding to a query audio content item; determine a query vector corresponding to the query audio content item; compare, in a vector space, the query vector and a plurality of target vectors corresponding to a plurality of target audio content items, to determine likelihood values indicating, for each respective target audio content item of the plurality of target audio content items, a probability that the respective target audio content item is a match for the query audio content item; identify at least one of the plurality of target audio content items having a highest of the likelihood values; and generate a new audio content item based on the query audio content item and the at least one of the plurality of target audio content items having the highest of the likelihood values. Claim 1: An audio content item identifier, comprising: at least one processor; and at least one memory storing instructions which when executed by the at least one processor cause the at least one processor to: receive, by a client device, a query corresponding to a query audio content item; determine a query vector corresponding to the query audio content item; compare, in a vector space, the query vector and a plurality of target vectors corresponding to a plurality of target audio content items, to determine likelihood values indicating, for each respective target audio content item of the plurality of target audio content items, a probability that the respective target audio content item is a match for the query audio content item, wherein the query audio content item and the target audio content items are audio stems that are configured to be inserted into an audio content item during an audio content item creation process; and output, to an editor tool, information identifying one of the plurality of target audio content items having a highest of the likelihood values. Claim 9: A method, comprising: receiving a query corresponding to a query audio content item; determining a query vector corresponding to the query audio content item; comparing, in a vector space, the query vector and a plurality of target vectors corresponding to a plurality of target audio content items, to determine likelihood values indicating, for each respective target audio content item of the plurality of target audio content items, a probability that the respective target audio content item is a match for the query audio content item; identifying at least one of the plurality of target audio content items having a highest of the likelihood values; and generating a new audio content item based on the query audio content item and the at least one of the plurality of target audio content items having the highest of the likelihood values. Claim 10: A method of identifying an audio content item, comprising: receiving, by a client device, a query corresponding to a query audio content item; determining a query vector corresponding to the query audio content item; comparing, in a vector space, the query vector and a plurality of target vectors corresponding to a plurality of target audio content items, to determine likelihood values indicating, for each respective target audio content item of the plurality of target audio content items, a probability that the respective target audio content item is a match for the query audio content item, wherein the query audio content item and the target audio content items are audio stems that are configured to be inserted into an audio content item during an audio content item creation process; and outputting, to an editor tool, information identifying one of the plurality of target audio content items having a highest of the likelihood values. Claim 17: A non-transitory computer-readable medium having stored thereon one or more sequences of instructions for causing one or more processors to perform: receiving a query corresponding to a query audio content item; determining a query vector corresponding to the query audio content item; comparing, in a vector space, the query vector and a plurality of target vectors corresponding to a plurality of target audio content items, to determine likelihood values indicating, for each respective target audio content item of the plurality of target audio content items, a probability that the respective target audio content item is a match for the query audio content item; identifying at least one of the plurality of target audio content items having a highest of the likelihood values; and generating a new audio content item based on the query audio content item and the at least one of the plurality of target audio content tems having the highest of the likelihood values. Claim 18: A non-transitory computer-readable medium having stored thereon one or more sequences of instructions for causing one or more processors to perform: receiving, by a client device, a query corresponding to a query audio content item; determining a query vector corresponding to the query audio content item; comparing, in a vector space, the query vector and a plurality of target vectors corresponding to a plurality of target audio content items, to determine likelihood values indicating, for each respective target audio content item of the plurality of target audio content items, a probability that the respective target audio content item is a match for the query audio content item, wherein the query audio content item and the target audio content items are audio stems that are configured to be inserted into an audio content item during an audio content item creation process; and outputting, to an editor tool, information identifying one of the plurality of target audio content items having a highest of the likelihood values. Examiner's Note 6. Vector space (According to Google): "A vector space is a mathematical structure consisting of a set of elements (vectors) that can be added together and multiplied by scalars (mumbers, usually real or complex). It must satisfy ten axioms, including closure under addition and scalar multiplication, commulativity, associativity, and the existence of zero and inverse vectors." Ellis et al, US 20130226957, [Ellis: Abstract and paragraph 6 ("identifying, using at least one hardware processor, a query song vector for the query song, wherein the query song vector is indicative of a two-dimensional Fourier transform based on the query song; identifying a plurality of reference song vectors that each correspond to one of a plurality of reference songs' ")] [Ellis: Paragraphs 6 and 19 ("determining a distance between the query song vector and each of the plurality of reference song vectors; generating an indication that a reference song corresponding to a reference song vector with a shortest distance to the query song vector is a similar song to the query song", i.e., comparing, in a vector space, the query vector and a plurality of target vectors a probability that the respective target audio content item is a match ..)] [Ellis: Paragraph 76 ("the distance between the query song vector and each of the reference song vectors can be found, and a predetermined number of reference songs with the smallest distance (e.g., one song, fifty songs, all reference songs, etc.) can be kept as similar songs", i.e., having a highest of the likelihood values ')] [Ellis: Paragraphs 51 and 52 ("distance between two vectors in the multi-dimensional space", i.e., 'in a vector space')]. Schnitzer, US 20110004642, [Schnitzer: Title and Abstract ("identifying similar audio tracks")] [Schnitzer: Paragraph 22 ("as may all tracks having a vector within a distance being a percentage of e.g. a maximum distance to all vectors or within a median of the distribution of distances", i.e., having a highest of the likelihood values')] [Schnitzer: Paragraph 127 ("To use FastMap to quickly process music recommendation queries, we initially use it to map the Gaussian timbre models to k-dimensional vectors. In a two step filter-and-refine process we then use those vectors as a prefilter: given a query object we first filter the whole collection in the vector space (with the squared Euclidean distance) to return a number (filter-size) of possible nearest neighbours.", ", i.e., 'in a vector space')]. Thagadur Shivappa et al, US 20180046431, [Thagadur Shivappa: Paragraph 154 (“If the cumulative value is not equal to a quantization value in a lookup table, the method 1000 may include determining a largest quantization value (Q) that does not exceed the cumulative value, at 1008, of retrieving parameters based on Q and generating a new version of the spatialized audio signal, at 1010, and updating the cumulative value based on an offset between Q and the cumulative value, at 1012. For example, referring to FIG. 1, the processor 104 may retrieve one or more of the sets of audio adjustment values 130 based on a largest quantization value (Q) that does not exceed the cumulative value 124, and may update the cumulative value 124 based on an offset between Q and the cumulative value 124.”)]. Conclusion 7. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136 (a) A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filled within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. 8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to [Hung D. Le], whose telephone number is [571-270-1404]. The examiner can normally be communicated on [Monday to Friday: 9:00 A.M. to 5:00 P.M.]. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Apu Mofiz can be reached on [571-272-4080]. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, contact [800-786-9199 (IN USA OR CANADA) or 571-272-1000]. Hung Le 06/22/2026 /HUNG D LE/Primary Examiner, Art Unit 2161
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Prosecution Timeline

Mar 20, 2025
Application Filed
Feb 06, 2026
Non-Final Rejection mailed — §DP
Apr 27, 2026
Interview Requested
May 04, 2026
Applicant Interview (Telephonic)
May 04, 2026
Response Filed
May 12, 2026
Examiner Interview Summary
Jun 25, 2026
Final Rejection mailed — §DP (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
90%
Grant Probability
96%
With Interview (+6.1%)
2y 4m (~1y 0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 1087 resolved cases by this examiner. Grant probability derived from career allowance rate.

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