DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12,306,864. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims are obvious variants as the independent claims of the instant invention are broader than the independent claims of Patent No. 12,306,864 as shown in the comparison table below.
Instant Application Claims
Patent No. 12,306,864
Claim 1. A method comprising:
obtaining, by a computing system provisioned with person data defining a list of person names, a text representation of a podcast episode and an audio representation of the podcast episode;
correlating, by the computing system, the person data with the text representation of the podcast episode to a person name from the list of the person names based on a text string within the text representation of the podcast episode;
matching, by the computing system in communication with a database storing a reference voice template for a voice corresponding to the person name, the audio representation of the podcast episode against the reference voice template, to detect presence in the podcast episode of the voice corresponding to the person name;
in response to detecting the voice corresponding to the person name in the podcast episode, generating, by the computing system, metadata to associate the person name with the podcast episode; and
outputting, by the computing system, the generated metadata.
Claim 1. A method comprising:
obtaining, by a computing system, a text representation of a podcast episode and an audio representation of the podcast episode; obtaining, by the computing system, person data defining a list of person names;
correlating, by the computing system, the person data with the text representation of the podcast episode, to find a match between (i) a person name from the list of the person names and (ii) a text string in the text representation of the podcast episode;
obtaining, by the computing system, at least one or more reference voice templates of a voice of a person having the person name; using, by the computing system, voice identification, including matching the audio representation of the podcast episode against the one or more voice templates, to detect presence in the podcast episode of the voice of the person having the person name;
based at least on the detecting in the podcast episode of the voice of the person having the person name, generating, by the computing system, metadata that associates the person name with the podcast episode; and
outputting, by the computing system, the generated metadata.
Claim 2
Claim 2
Claim 3. The method of claim 1, further comprising: determining, by the computing system utilizing machine-learning-based role identification, a role of the person in the podcast episode; and based on the determined role of the person in the podcast episode, generating, by the computing system, additional metadata to identify the role of the person in the podcast episode, wherein outputting by the computing system the generated metadata further includes outputting by the computing system the additional metadata when generated.
Claim 3. The method of claim 1, further comprising: using, the computing system, machine-learning-based role identification to determine a role of the person in the podcast episode; and based on the determined role of the person in the podcast episode, generating, by the computing system, additional metadata that identifies the role of the person in the podcast episode, wherein outputting by the computing system the generated metadata includes outputting by the computing system the generated additional metadata.
Claim 4
Claim 4
Claim 5. The method of claim 1, further comprising: using, by the computing system, voice identification on at least a part of the audio representation as a basis to determine one or more times in the podcast episode when the voice corresponding to the person is present; and generating and outputting, by the computing system, additional metadata indicating the one or more determined times.
Claim 5. The method of claim 1, further comprising: using, by the computing system, voice identification as a basis to determine one or more times in the podcast episode when the voice of the person is present; and generating and outputting, by the computing system, additional metadata indicating the one or more determined times.
Claim 6
Claim 6
Claim 7. The method of claim 1, further comprising: searching, based on the generated metadata, one or more the podcast episode for the person name.
Claim 7. The method of claim 1, further comprising using the generated metadata as a basis to facilitate podcast searching based on the person name.
Claim 8. A computing system comprising: one or more processors; non-transitory data storage; and program instructions stored in the non-transitory data storage and executable by the one or more processors to carry out operations including:
obtaining a text representation of a podcast episode and an audio representation of the podcast episode,
obtaining person data defining a list of person names,
correlating the person data with the text representation of the podcast episode to a person name from the list of the person names based on a text string within the text representation of the podcast episode,
obtaining at least a reference voice template of a voice corresponding to a person name,
matching the audio representation of the podcast episode against the reference voice template, to detect presence in the podcast episode of the voice corresponding to the person name,
based at least on the detecting in the podcast episode of the voice of the person having the person name, generating metadata that associates the person name with the podcast episode, and
outputting the generated metadata.
Claim 8. A computing system comprising: one or more processors; non-transitory data storage; and program instructions stored in the non-transitory data storage and executable by the one or more processors to carry out operations including:
obtaining, by a computing system, a text representation of a podcast episode and an audio representation of the podcast episode,
obtaining person data defining a list of person names,
correlating the person data with the text representation of the podcast episode, to find a match between (i) a person name from the list of the person names and (ii) a text string in the text representation of the podcast episode,
obtaining at least one or more reference voice templates of a voice of a person having the person name,
using voice identification, including matching the audio representation of the podcast episode against the one or more voice templates, to detect presence in the podcast episode of the voice of the person having the person name,
based at least on the detecting in the podcast episode of the voice of the person having the person name, generating metadata that associates the person name with the podcast episode, and
outputting the generated metadata.
Claims 9-13
Claims 9-13
Claim 14. The computing system of claim 8, wherein the operations additionally include: searching, based on the generated metadata, one or more podcast episode for the person name.
Claim 14. The computing system of claim 8, wherein the operations additionally include using the generated metadata as a basis to facilitate podcast searching based on the person name.
Claim 15 (similar to claim 8)
Claim 15
Claims 16-19
Claims 16-19
Claim 20. The non-transitory computer-readable medium of claim 15, wherein the operations additionally comprise: searching, based the generated metadata, one or more podcast episode for the person name.
Claim 20. The non-transitory computer-readable medium of claim 15, wherein the operations additionally comprise using the generated metadata as a basis to facilitate podcast searching based on the person name.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3-5 and 7-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 3 recites the limitation "the person" in line 4. There is insufficient antecedent basis for this limitation in the claim as claim 1 discloses person data, a person name and person names, but not a person. Claim 4 is also rejected for its dependency on claim 3.
Claim 5 recites the limitation "the person" in line 4. There is insufficient antecedent basis for this limitation in the claim as claim 1 discloses person data, a person name and person names, but not a person.
Claim 7 recites the limitation "the person" in line 2. There is insufficient antecedent basis for this limitation in the claim as claim 1 discloses person data, a person name and person names, but not a person.
Claims 8 and 15 recite the limitation "the person" in lines 17 and 14, respectively. There is insufficient antecedent basis for this limitation in the claims as the claims discloses person data, a person name and person names, but not a person. Claims 9-14 and 16-20 are also rejected for their dependency on claims 8 and 15, respectively.
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.
Claim(s) 1, 5-8, 12-15, 19 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Adlersberg et al. (U.S. Patent No. 11334618; hereinafter Adlersberg) in view of Milavsky et al. (U.S. PG Pub No. 2019/0327524; hereinafter Milavsky) and further in view of Garg et al. (U.S. PG Pub No. 2022/0115029; hereinafter Garg).
Regarding claim 1, Adlersberg discloses a method comprising:
obtaining, by a computing system provisioned with person data defining a list of person names, a text representation and an audio representation (Col. 2, Lines 20-36; Col. 3, Lines 55-67; Col. 6, Lines 41-67: the system stores a list or table of names of participants of an audio conversation in a repository of the system; and audio recording of an audio conversation (e.g., such as a podcast) is received and a generated transcript (e.g., such as a text representation) of the audio), but fails to explicitly disclose of a podcast episode;
correlating, by the computing system, the person data with the text representation based on a text string within the text representation (Col. 2, Lines 20-36; Col. 3, Lines 55-67; Col. 6, Lines 41-67; Col. 10, Lines 34-41: the names of participants of an audio conversation are analyzed against the transcript of the audio to determine the speaker/name based on the corresponding spoken audio), but fails to explicitly disclose of the podcast episode and to a person name from the list of the person names;
matching, by the computing system in communication with a database storing a reference voice template for a voice corresponding to the person name, the audio representation against the reference voice template, to detect presence of the voice corresponding to the person name (Col.4, Lines 35-59; Col. 9, Lines 36-65: utilizes an audio signature/profile that is pre-constructed for each participant to correlate a particular audio time-slot with its respective speaker by name), but fails to explicitly disclose of the podcast episode;
in response to detecting the voice corresponding to the person name, generating, by the computing system, metadata to associate the person name with (Col. 9, Lines 36-65: after correlating a particular audio time-slot with its respective speaker by name, a tag/name attribute/metadata is generated, associated and stored for the speaker), but fails to explicitly disclose of the podcast episode.
Adlersberg also fails to disclose outputting, by the computing system, the generated metadata.
However, Milavsky discloses correlating, by the computing system, the person data with the text representation to a person name from the list of the person names based on a text string within the text representation ([0013], [0016]-[0020] compares speaker identification data to a known reference list of speakers for audio media and text transcript), but fails to disclose of the podcast episode.
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg and Milavsky before him/her, to modify the teachings of Adlersberg with the teachings of Milavsky. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker detection of Milavsky to determine the impact of audio sources on media monitoring metrics as disclosed by Milavsky [0009].
The combination of Adlersberg and Milavsky fails to disclose, however, Garg discloses a podcast episode and outputting, by the computing system, the generated metadata ([0097] system output of podcast content generated metadata).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg, Milavsky and Garg before him/her, to modify the teachings of Adlersberg with the teachings of Garg. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker identification of Garg to utilize speaker labels/metadata to help in find a match for content as disclosed by Garg [0078].
Regarding claim 5, the combination of Adlersberg, Milavsky and Garg discloses the method of claim 1, further comprising: using, by the computing system, voice identification on at least a part of the audio representation as a basis to determine one or more times in the podcast episode when the voice corresponding to the person is present; and generating and outputting, by the computing system, additional metadata indicating the one or more determined times (Adlersberg: Col. 2, Lines 20-36; Col. 4, Line 60 - Col. 5, Line 6; Col. 6, Lines 41-67: captures start and end times of the person talking throughout the audio; Garg: [0097]).
Regarding claim 6, the combination of Adlersberg, Milavsky and Garg discloses the method of claim 5, wherein in the additional metadata comprises, for each of the one or more identified times, a start timestamp and an end timestamp (Adlersberg: Col. 2, Lines 20-36; Col. 4, Line 60 - Col. 5, Line 6; Col. 6, Lines 41-67: captures start and end times of the person talking throughout the audio).
Regarding claim 7, the combination of Adlersberg, Milavsky and Garg discloses the method of claim 1, further comprising: searching, based on the generated metadata, one or more the podcast episode for the person name (Adlersberg: Col. 2, Lines 20-36; Col. 9, Line 36 - Col. 10, Line 11; Col. 13, Lines 8-15: names/metadata of speakers/persons can be searched; Garg: [0097]).
Regarding claim 8, Adlersberg discloses a computing system comprising: one or more processors; non-transitory data storage; and program instructions stored in the non-transitory data storage and executable by the one or more processors to carry out operations including (Col. 14, Lines 14-63):
obtaining a text representation of a podcast episode and an audio representation of the podcast episode (Col. 2, Lines 20-36; Col. 3, Lines 55-67; Col. 6, Lines 41-67), but fails to explicitly disclose of a podcast episode,
obtaining person data defining a list of person names (Col. 2, Lines 20-36; Col. 3, Lines 55-67; Col. 6, Lines 41-67),
correlating the person data with the text representation to a person name based on a text string within the text representation (Col. 2, Lines 20-36; Col. 3, Lines 55-67; Col. 6, Lines 41-67; Col. 10, Lines 34-41), but fails to explicitly disclose of the podcast episode and to a person name from the list of the person names,
obtaining at least a reference voice template of a voice corresponding to a person name (Col.4, Lines 35-59; Col. 9, Lines 36-65),
matching the audio representation against the reference voice template, to detect presence of the voice corresponding to the person name (Col.4, Lines 35-59; Col. 9, Lines 36-65), but fails to explicitly disclose of the podcast episode,
based at least on the detecting of the voice of the person having the person name, generating metadata that associates the person name (Col. 9, Lines 36-65), but fails to explicitly disclose the podcast episode.
Adlersberg also fails to disclose outputting the generated metadata.
However, Milavsky discloses correlating the person data with the text representation to a person name from the list of the person names based on a text string within the text representation ([0013], [0016]-[0020]), but fails to disclose of the podcast episode.
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg and Milavsky before him/her, to modify the teachings of Adlersberg with the teachings of Milavsky. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker detection of Milavsky to determine the impact of audio sources on media monitoring metrics as disclosed by Milavsky [0009].
The combination of Adlersberg and Milavsky fails to disclose, however, Garg discloses a podcast episode and outputting the generated metadata ([0097]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg, Milavsky and Garg before him/her, to modify the teachings of Adlersberg with the teachings of Garg. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker identification of Garg to utilize speaker labels/metadata to help in find a match for content as disclosed by Garg [0078].
Regarding claim 12, the combination of Adlersberg, Milavsky and Garg discloses the computing system of claim 8, wherein the operations additionally include: using voice identification as a basis to determine one or more times in the podcast episode when the voice of the person is present; and generating and outputting additional metadata indicating the one or more determined times (Adlersberg: Col. 2, Lines 20-36; Col. 4, Line 60 - Col. 5, Line 6; Col. 6, Lines 41-67: captures start and end times of the person talking throughout the audio; Garg: [0097]).
Claims 13-15, 19 and 20 contain corresponding limitations as claims 6-8 and 12 and are therefore rejected for the same rationale.
Claim(s) 2, 9 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Adlersberg et al. (U.S. Patent No. 11334618; hereinafter Adlersberg) in view of Milavsky et al. (U.S. PG Pub No. 2019/0327524; hereinafter Milavsky) in view of Garg et al. (U.S. PG Pub No. 2022/0115029; hereinafter Garg) and further in view of Khoury et al. (U.S. PG Pub No. 2021/0326421; hereinafter Khoury).
Regarding claim 2, the combination of Adlersberg, Milavsky and Garg discloses the method of claim 1, wherein the person names in the list defined by the person data are names of people (Adlersberg: Col. 2, Lines 20-36; Milavsky: [0013], [0016]-[0020]), but fails to disclose, however, Khoury discloses the method further comprising: filtering, by the computing system, the person data based on accreditations of the people ([0081], [0113] subscription information (e.g., such as memberships/accreditations) is queried in speaker profiles to identify subscriber information for speakers).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg, Milavsky, Garg and Khoury before him/her, to modify the teachings of Adlersberg with the teachings of Khoury. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker utterance/recognition of Khoury for enrolling new speakers as a service operates and to providing content or configuring edge device for speakers with pre-established and/or non-established speaker profiles so a system can differentiate the profiles from each other for utterance matching as disclosed by Khoury [0011].
Claims 9 and 16 contain corresponding limitations as claim 2 and are therefore rejected for the same rationale.
Claim(s) 3, 4, 10, 11, 17 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Adlersberg et al. (U.S. Patent No. 11334618; hereinafter Adlersberg) in view of Milavsky et al. (U.S. PG Pub No. 2019/0327524; hereinafter Milavsky) in view of Garg et al. (U.S. PG Pub No. 2022/0115029; hereinafter Garg) and further in view of Blandin et al. (U.S. PG Pub No. 2017/0169816; hereinafter Blandin).
Regarding claim 3, the combination of Adlersberg, Milavsky and Garg discloses the method of claim 1, further comprising: wherein outputting by the computing system the generated metadata further includes outputting by the computing system the additional metadata when generated (Adlersberg: Col. 9, Lines 36-65; Garg: [0097]), but fails to disclose, however, Blandin discloses determining, by the computing system utilizing machine-learning-based role identification, a role of the person in the podcast episode; and based on the determined role of the person in the podcast episode, generating, by the computing system, additional metadata to identify the role of the person in the podcast episode ([0022], [0029], [0045] identifies and tags/labels a speaker in the event audio based on their role as a leader, guest, etc.).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg, Milavsky, Garg and Blandin before him/her, to modify the teachings of Adlersberg with the teachings of Blandin. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker identification of Blandin for using pre-established voice signatures and identity information to identify statements by persons of importance in order to effectively make use of the additional contextual information available about the event as disclosed by Blandin [0013], [0016].
Regarding claim 4, the combination of Adlersberg, Milavsky, Garg and Blandin discloses the method of claim 3, wherein the role comprises at least one item selected from the group consisting of a host of the podcast episode, a guest of the podcast episode, and a subject of the podcast episode (Blandin: [0022], [0029], [0045]; Garg: [0097]).
Regarding claim 10, the combination of Adlersberg, Milavsky and Garg discloses the computing system of claim 8, wherein the operations additionally include: wherein outputting the generated metadata includes outputting the generated additional metadata (Adlersberg: Col. 9, Lines 36-65; Garg: [0097]), but fails to disclose, however, Blandin discloses determining using machine-learning-based role identification a role of the person in the podcast episode, and based on the determined role of the person in the podcast episode, generating additional metadata that identifies the role of the person in the podcast episode ([0022], [0029], [0045]).
Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains, having the teachings of Adlersberg, Milavsky, Garg and Blandin before him/her, to modify the teachings of Adlersberg with the teachings of Blandin. The motivation for doing so would combine the audio speaker recognition of Adlersberg with the audio speaker identification of Blandin for using pre-established voice signatures and identity information to identify statements by persons of importance in order to effectively make use of the additional contextual information available about the event as disclosed by Blandin [0013], [0016].
Claims 11, 17 and 18 contain corresponding limitations as claims 4 and 10 and are therefore rejected for the same rationale.
Support for Amendments and Newly Added Claims
Applicants are respectfully requested, in the event of an amendment to claims or submission of new claims, that such claims and their limitations be directly mapped to the specification, which provides support for the subject matter. This will assist in expediting compact prosecution and reducing potential 35 USC § 112(a) or 35 USC § 112, 1st paragraph issues that can arise when claims are amended. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.121(b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as “Applicants believe no new matter has been introduced” may be deemed insufficient. The examiner thanks the Applicant in advance for providing support for any amendments or newly added claims.
Examiner cites particular columns and line numbers or paragraphs in the references as applied to claims above for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may be applied as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DIEDRA M MCQUITERY whose telephone number is (571)272-9607. The examiner can normally be reached Monday - Thursday, 8 am - 6 pm (C.S.T.).
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/Diedra McQuitery/Primary Examiner, Art Unit 2166