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 .
Response to Arguments
Applicant's arguments have been fully considered but they are not persuasive for the following reasons:
No claim has been allowed or indicated as being allowable in this application. The double patenting rejection will remain on record until the issue is resolved.
Regarding the 101 issue, Examiner discussed in a previous communication that the steps of “determining … whether each segment in the text is topical or non-topical …”, “identifying a position within the text that changes from topical to non-topical …”, “identifying a non-narrative portion with the text …”, and “generating a clean text …” can be performed by a human user without the aid of a machine. Specifically, a human being can manually inspect a text and determine whether it is topical or non-topical, and its boundary or position separating topical from non-topical and then generate an output text containing only narrative portion. The claims lack specificity to the degree that they give the human user free hand in performing the steps. The additional step of “retrieving … a text …” and the additional element of “a trained language model” are merely for the purpose of data gathering and/or insignificant extra-solution activity that amount to no more than mere instructions to apply the exception using a generic computer component. The Examiner also analyzed dependent claims using the same analysis applied to the independent claims. Although the dependent claims include additional limitations or elements, those limitations lack sufficient specificity such that they, too, can also be performed by a human user without the aid of a machine. For at least these reasons, examiner maintains the 101 rejection.
In response to applicant’s argument that the prior art of record does not teach a language model used to determine whether each text segment is topical or non-topical, the Examiner submits that, in the absence of further specificity, the claimed “language model” was interpreted as a lexicon of model words used to detect or identify stopwords for determining whether a text segment is topical or non-topical (paragraphs 32-33 and 38, “Stopword detector 62 may assign a binary value BV(i) to each ith word depending on whether or not it is a stopword. For example, it may assign a value of 1 to the word if it is a stopword, and a value of 0 if it is not a stopword. The flow of text is thus "translated" into a series of binary values representing the occurrence of stopwords and their positions in the text.”; to detect or identify stopwords, a lexicon containing model words must exist for comparison and matching against the words in the text segment).
Independent claim 11 recites “using the identification of the non-narrative portions, providing the media content item to a user as a recommendation.” The claimed “media content item” is a content from which the narrative and non-narrative portions are identified. The subsequent limitation merely recites “using the identification of the non-narrative portions” when providing the media content item to the user as a recommendation. However, the claim does not specify how the identification is used to provide the recommendation, nor does it require that the identification affect the selection of the media content item to be recommended. Thus, the claim language does not establish a causal relationship between the identification of the non-narrative portion and the recommendation of the medica content item; the media content item may remain the same content item that was retrieved and provided as the input to the identification process.
Regarding claim 19, the same deficiency exists in the limitation reciting “using the identification of the non-narrative portions, providing a description of the media content item to a user.” The media content item itself may constitute the claimed “description.” In such a case, identifying the non-narrative portions does not necessarily produce or modify the description provided to the user. Rather, the media content item that serves as the input for identifying the narrative and non-narrative portions may itself be provided to the user as the claimed description. The claim does not specify how the identification of the non-narrative portions is used to generate, modify, select, or otherwise affect the description provided to the user. Accordingly, the recited “using” language does not establish a substantive causal relationship between the identification of the non-narrative portions and the description provided to the user.
For the above reasons, examiner maintains all previous grounds of rejection.
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.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 2-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12124507. Although the claims at issue are not identical, they are not patentably distinct from each other because they are obvious variants of the same invention, and the claims of the patent are narrower in scope and anticipate the claims of the application.
Claims of application Claims of the patent
2. (New) A method, comprising:
retrieving, from a database, a text that corresponds to audio from a media content item that is provided by a media providing service, the text comprising a plurality of segments;
determining, by applying the text to a trained language model, whether each segment in the text is topical or non-topical relative to a narrative of the media content item;
identifying a position within the text that changes from topical to non-topical, wherein two consecutive segments;
identifying a non-narrative portion within the text using the identified position; and
generating a clean text, including removing the non-narrative portion from the text based at least in part on the identified position within the text.
3. (New) The method of claim 2, wherein determining whether each segment in the text is topical or non-topical relative to the narrative of the media content item comprises classifying each segment in the text as topical or non-topical relative to the narrative of the media content item.
4. (New) The method of claim 2, wherein the text includes a transcript of audio content of the media content item, and the method further comprises: generating a description of the media content item based on the clean text.
5. (New) The method of claim 2, further comprising: providing the media content item associated with the text to a user of the media providing service based at least in part on the generated clean text.
6. (New) The method of claim 2, wherein: the trained language model is trained on a plurality of annotated texts; and each of the annotated texts in the plurality of annotated texts includes text corresponding to audio from a media content item of a plurality of media content items and a plurality of annotations.
7. (New) The method of claim 6, wherein: each annotated text of the plurality of annotated texts includes an annotation for each segment in the text corresponding to audio from a media content item of the plurality of media content items.
8. (New) The method of claim 6, further comprising: for a respective annotated text, generating a label for each segment in the respective annotated text based on at least a portion of the plurality of annotations.
9. (New) The method of claim 2, wherein: determining a segment in the text is topical or non-topical relative to a narrative of the media content item includes analyzing content of the segment.
10. (New) The method of claim 2, wherein: determining a segment in the text is topical or non-topical relative to a narrative of the media content item includes analyzing content of the segment and content of a segment preceding the segment.
Other claims are similar to the above claims.
1. A method, comprising:
retrieving, from a database, a text that corresponds to audio from a media content item that is provided by a media providing service, the text comprising a plurality of segments;
assigning, by applying the text to a trained language model, a score for each segment in the text, wherein the score corresponds to a predicted relevance of the respective segment to a narrative of the media content item;
identifying a change position within the text that corresponds to a difference in scores of two consecutive segments, wherein: the change position is located between the two consecutive segments;
using the assigned scores, identifying a non-narrative segment within the text; and
generating a clean text, including removing the non-narrative segment from the text based at least in part on the identified change position within the text.
2. The method of claim 1, wherein the text includes a transcript of audio content of the media content item, and the method further comprises: generating a description of the media content item based on the clean text.
3. The method of claim 1, further comprising: providing the media content item associated with the text to a user of the media providing service based at least in part on the generated clean text.
4. The method of claim 1, wherein: the trained language model is trained on a plurality of annotated texts; and each of the annotated texts in the plurality of annotated texts includes text corresponding to audio from a media content item of a plurality of media content items and a plurality of annotations.
5. The method of claim 4, wherein: each annotated text of the plurality of annotated texts includes an annotation for each segment in the text corresponding to audio from a media content item of the plurality of media content items.
6. The method of claim 4, further comprising: for a respective annotated text, generating a label for each segment in the respective annotated text based on at least a portion of the plurality of annotations.
7. The method of claim 1, wherein: assigning a score for a segment in the text includes analyzing content of the segment.
8. The method of claim 1, wherein: assigning a score for a segment in the text includes analyzing content of the segment and content of a segment preceding the segment.
Other claims are similar to the above claims.
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 2-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims 2, 11, and 19 recite “determining … topical or non-topical …”, “identifying a position…”, “identifying a non-narrative portion …”, and “generating a clean text …”. These limitations, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “processors” and “a trained computational model”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “processors” language, these steps in the context of this claim encompasses the user manually inspecting a text and determining whether it is topical or non-topical, and its boundary or position separating topical from non-topical, and generating an output text containing only narrative portion. All of these steps can be performed in the mind and/or using a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements - using a processor and/or “a trained computational model” to perform all these steps. The use of a processor is recited at a high-level of generality (i.e., as a generic computer device performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The claim does 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 step of “retrieving …” and additional element of “a trained language model” are merely for the purpose of data gathering and/or insignificant extra-solution activity that amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Dependent claims 3-10, 12-18, and 20-21 include addition steps that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components in the context of this claim encompasses the user manually performing these steps. All of these steps can be performed in the mind and/or using a pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 2-5, 9-13, and 17-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Amitay et al. (USPG 2006/0161537, hereinafter Amitay).
Regarding claim 2, 11, and 19, Amitay discloses a method, device, and non-transitory CRM, comprising: one or more processors; and memory storing one or more programs, the one or more programs including instructions, which when executed by the one or more processors (paragraphs 26-31), cause the electronic device to perform a set of operations, comprising:
retrieving, from a database, a text that corresponds to audio from a media content item that is provided by a media providing service, the text comprising a plurality of segments (figure 1 and/or paragraphs 26-27, processing text documents);
determining, by applying the text to a trained language model, whether each segment in the text is topical or non-topical relative to a narrative of the media content item (paragraphs 32-33, topical text and non-topical text depend on closed class words or stopword; the process for determining is discussed in paragraphs 37-41);
identifying a position within the text that changes from topical to non-topical, wherein two consecutive segments (paragraphs 42-48, “peaks and valleys” are positions);
identifying a non-narrative portion within the text using the identified position (paragraphs 42-48, “peaks and valleys” represents narrative and non-narrative portions; see graph in figure 5);
generating a clean text, including removing the non-narrative portion from the text based at least in part on the identified position within the text (figure 2, step 36; only narrative text is used to generate a final text output; Also see paragraph 28); and
using the identification of the non-narrative portions, providing the media content item to a user as a recommendation or providing a description of the media content item to a user (paragraph 30, the text processor 39 functions to mark segments of the media content as either narrative or non-narrative; see Response to Arguments section above for detailed discussion).
Regarding claims 3-5, 11-13, and 20, Amitay further discloses wherein determining whether each segment in the text is topical or non-topical relative to the narrative of the media content item comprises classifying each segment in the text as topical or non-topical relative to the narrative of the media content item (paragraphs 42-48, “peaks and valleys” represents narrative and non-narrative portions; see graph in figure 5); wherein the text includes a transcript of audio content of the media content item, and the method further comprises: generating a description of the media content item based on the clean text (paragraphs 27 and 30, transcription of speech); further comprising: providing the media content item associated with the text to a user of the media providing service based at least in part on the generated clean text (paragraphs 26-27 and 30, “text processor 39 may provide a different marking on the transcription or may mark up the video for each type of speech.”).
Regarding claims 9-10, 17-18, and 21, Amitay further discloses wherein: determining a segment in the text is topical or non-topical relative to a narrative of the media content item includes analyzing content of the segment (paragraphs 32-33 and 42-48, processing the text to determine “peaks and valleys” that represent narrative and non-narrative portions; see graph in figure 5); and wherein: determining a segment in the text is topical or non-topical relative to a narrative of the media content item includes analyzing content of the segment and content of a segment preceding the segment (paragraphs 39-41; taking into account adjacent words).
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 6-8 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Amitay in view of Somasundaran et al. (USPN 10380490, hereinafter referred to as Somasundaran).
Regarding claims 6-8 and 14-16, Amitay fails to explicitly disclose, however, Somasundaran teaches wherein: the trained language model is trained on a plurality of annotated texts (process in figure 1, training model in step 170; also see col. 3, lines 28-53 and col. 5, lines 8-32, “human annotators” assign score the narratives to train the model as shown in figure 2); and each of the annotated texts in the plurality of annotated texts includes text corresponding to audio from a media content item of a plurality of media content items and a plurality of annotations (figure 1 and/or col. 3, line 28 to col. 4, line 24); wherein: each annotated text of the plurality of annotated texts includes an annotation for each segment in the text corresponding to audio from a media content item of the plurality of media content items (process in figure 1, training model in step 170; also see col. 3, lines 28-53 and col. 5, lines 8-32, “human annotators” assign score the narratives to train the model as shown in figure 2); further comprising: for a respective annotated text, generating a label for each segment in the respective annotated text based on at least a portion of the plurality of annotations (process in figure 1 uses human annotated narratives to train model, and then use the trained model to new text to determine narrative and non-narrative sections).
Since Amitay and Somasundaran are analogous in the art because they are from the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to use the known technique of applying annotated narrative to train model. One of ordinary skill in the art would have recognized that the results of the combination were predictable since the use of that known technique provides the rationale to arrive at a conclusion of obviousness. See KSR International Co. v. Teleflex Inc., 82 USPQ2d 1385 (U.S. 2007).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Doggett et al. (USPG 2019/0384826) teach assigning a narrative score to each word and then determining whether the word is narrative based on the narrative score of each word that is considered pertinent to the claimed invention.
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 filed 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 nonprovisional extension fee (37 CFR 1.17(a)) 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUYEN X VO whose telephone number is (571)272-7631. The examiner can normally be reached M-F, 8-4.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bhavesh Mehta can be reached on 571-272-7453. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HUYEN X VO/Primary Examiner, Art Unit 2656
