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 Amendment
In response to the Advisory Action from 3/16/2026, Applicant has filed a Request for Continued Examination (RCE) on 4/8/2026. In this reply, Applicant has amended independent claim 1 to further add details of the first interface (i) comprising a plurality of inputs each corresponding to a different candidate feature identified based upon the analysis of the first content item and (ii) enabling a user of the podcast customization interface to concurrently select multiple candidate features identified based upon the analysis of the first content item in association with the first podcast customizing feature. Claims 11 and 16 feature broader amendments that do not require the customization of the interface based upon analysis of the first content item and instead relate to a more generic dynamic interface.
Applicant has also argued that the prior art of record fails to teach the limitations added to claim 1 even though these limitations are not present in independent claims 11 and 16 (Remarks, Pages 8-13). These arguments have been fully considered, however, are not found to be persuasive for the reasons noted in the below Response to Arguments section.
Response to Arguments
In regards to amended Claim 1, Applicant arguments related to the secondary reference Basu, et al. (U.S. PG Publication: 2008/0300872 A1) that is summarized and then described as not allowing "the user to concurrently select multiple keywords in association with a (single) customizing feature, as doing so would not appear to make sense since each keyword could correspond to a different portion of the video, for example" (Remarks, Pages 9-12). Applicant further argues that additional features in Basu such as volume control and play speed are built into a browsing interface rather than being identified based upon analysis of content (Remarks, Page 13). In this manner Applicant concludes that Baus in a combination with Gardner fails to teach the invention set forth in claim 1.
In response, since Basu was used to address the interface generated based upon content analysis and Applicant's arguments are directed towards the teachings of Basu, the following remarks will be aimed at the teachings of Basu though keeping in mind that Basu was used in a combination with the primary reference Gardner. Specifically, Basu describes audio summary playback/rendering based upon a number of concurrently selectable factors populated in an interface and based upon speech analysis/classification of input content such as topic, keywords, and speaker turn. See for example multiple instances of such discussion in Basu-
Ability of a user to select "a group of keywords" based upon a topic for playback (Paragraph 0054)
Example of a user selection of multiple steps related to terms to generate a playback summary of solving a mathematical problem while cutting out tangential conversation (Paragraph 0062).
Indicating that content for selection/summarization can be based upon multiple factors such as "topic" or a particular "speaker" (Paragraphs 0057 and 0067).
Describing the selection of "a number of keywords that provide a summary of the spoken conversation" (Paragraph 0070).
Describing methodology 1100 provides for control over the level of detail of a summary or portions thereof, defined by topic, turn, and/or sequential boundaries (Paragraph 0073).
Thus, while there are some sections of drill-down in Basu of playback/rendering based upon a singular keyword and interface features that are pre-populated such as volume and speed, in multiple instances Basu's interface allows for the selection of multiple features generated from analyzing input content such as topic, speaker, keywords, etc. (see also the example of the mathematics-related summary). When taken in a combination with Gardner, Basu's interface predictably allows for the ability to control podcast generation/content summarization based upon content portions associated with a keyword, topic, and person of interest. Thus, Applicant arguments directed towards claim 1 are not found to be persuasive.
The remaining independent and dependent claims have been traversed for reasons similar to claim 1 (Remarks, Pages 8 and 13-14). In response to the arguments directed towards independent claims 11 and 16, Applicant is reminded that claims 11 and 16 are of a broader scope than claim 1 and do not include the interface specifics relied upon in the Applicant’s claim 1 arguments. Thus, these arguments are considered unpersuasive and moot. In regards to the remaining dependent claims, Applicant is directed towards the response directed towards claim 1.
In order to differentiate Applicant’s claimed invention from the prior art, it might be useful if Applicant included what information is being extracted from the content and how it is used to populate the interface in the claimed invention.
Without specific supporting rationale, Applicant alleges that independent claims 11 and 16 as amended "are believed to be directed towards statutory subject matter" (Remarks, Page 8).
These arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Since claims 11 and 18 lack the specific interface details that direct claim 1 towards patent eligible subject matter under 35 U.S.C. 101 in favor of a more generic computer interface that does not include such technical computer interface improvements, these claims remain directed towards patent ineligible subject matter for the reasons noted in the proceeding rejection.
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 11-12 and 14-20 are rejected under 35 U.S.C. 101 for being directed towards a patent ineligible mental process under the broadest reasonable interpretation.
Independent claims 11 and 16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims regard a process that, as drafted under its broadest reasonable interpretation, covers performance of the limitations as a mental process, but for the recitation of generic computer components.
In regards to the process of claims 11 and 16 the claimed functionality could be practiced as a mental process in the following manner:
request to provide a podcast to a client device, wherein the request is indicative of the podcast customizing feature (a human such as a podcaster can receive a written list of a podcast to be recording specifying the topic and style indications (e.g., length of time, segments, emotions/reactions, etc.)), wherein ;
determining, based upon the request, a set of content items (the human can review the documentation and mentally decide upon a content items that will be covered in the podcast and can write a script using pen and paper);
generating a summary of the set of content items based upon the podcast customizing feature (a human narrows down the content such as a podcast script based upon e.g., audience interests, time constraints, etc.);
generating the podcast to comprise an auditory representation of the summary (a human podcaster can read out the narrowed down script with potential improvisation); and
providing the podcast to the client device (human speaks the script while a recording device on a client device is on- note that the BRI of this step relates to human performance where the device is passive and not performing any processing; note also that claim 11 relates to an article that can be considered and read out by a human podcaster to generate a podcast while claim 16 relates to a requested summary podcast based upon a second podcast where a human podcaster can listen to a second podcast, remember the contents, and then summarize that podcast to generate the first podcast).
This judicial exception is not integrated into a practical application. Outside of the identified abstract idea, the claimed invention only includes computer components (e.g., a processor, memory, non-transitory machine-readable medium, and a dynamic user interface used for data gathering) which amount to no more than mere instructions to implement an otherwise abstract idea using generic computer components and interfaces. While these claims have been amended to include additional features of an interface, the particular details of generating that interface are missing from the claimed invention where the interface is not particularly structured to lead to an improvement in technology. Instead, the interface merely provides for preference input in a general manner. Applicant did not invent or improve the ability to input menu options or provide user preferences/settings into a generic computer interface. Accordingly, the claimed invention does not improve the use of a computer as a tool, it only relies upon the computer for its known purpose of data input/gathering and executing a program to carry out an otherwise abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The above identified additional generic computer components are no more than mere instructions to apply the exception using generic computer components that are well-known, routine, and conventional as is evidenced by Bancorp Services v. Sun Life (Fed. Cir. 2012) and Alice Corp. v. CLS Bank (2014). In regards to the use of a generic computer interface that allows the user to input pertinent data and responds to user data dynamically or arranges data dynamically on a GUI failing to amount to an inventive concept, see Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) and Trading Technologies v. IBG LLC, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019).
Accordingly, independent 11 and 16 are directed towards patent ineligible subject matter under 35 U.S.C. 101.
The remaining dependent claims fail to add patent eligible subject matter to their respective parent claims;
Claim 12 regards a generic computer interface for providing the customization data.
Claims 14 and 18 narrow the recited content and customization features that can be considered by a human when reading content and generating a summary script and/or relate to a generic computer interface for reception of such features.
Claim 15 and 19 regard the use of a generic language model recited at a high level for generating the summary that is otherwise performed by a human. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to 8 perform an existing process; and (3) the particularity or generality of the application of the judicial exception. In the instant claim, the use of a language model only presents the idea of a solution (i.e., generating a summary) while failing to describe how the process for how the language model is used to achieve the solution. Moreover, use of a language model for summarization is well-known per the teachings of Aggarwal, et al. (U.S. PG Publication: 2020/0380403 A1, Paragraph 0003), Coursey (U.S. Patent: 11,645,479, Col. 6, Line 59- Col. 7, Line 4), and Karadimitriou, et al. (U.S. PG Publication: 2023/0315955 A1, Paragraph 0042).
Claim 17 regards a person listening to a second podcast and transcribing the content using pen and paper.
Claim 20 regards generic computer automation of manual speech production.
Claim Rejections - 35 USC § 102
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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 11-12 and 14-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Gardner, et al. (U.S. Patent: 12,008,332).
With respect to Claim 11, Gardner discloses:
A computing device comprising: a processor; and memory comprising processor-executable instructions that when executed by the processor cause performance of operations (method implementation as a system having a processor and memory storing program instructions, Col. 66, Lines 9-42), the operations comprising:
generating a podcast customization interface comprising a first dynamic interface for submitting an indication of a podcast customizing feature ("interactive interfaces allow users to dynamically control and customize the summarization on demand" generated on a display, Col. 19, Lines 32-64; see also interfaces allowing for dynamic customization in Col. 20, Lines 29-33 and the discussion of levels of abstraction in the interface dynamically determined in Col. 24, Lines 39-50; further see Col. 28, Lines 39-44 and Col. 32, Lines 60-63), and receiving, via the podcast customization interface, a request to provide a podcast to a client device, wherein the first dynamic interface (i) comprises a plurality of inputs each corresponding to a different candidate feature and (ii) enables concurrent selection of multiple candidate features in association with the podcast customizing feature wherein the request is indicative of: an article; and the podcast customizing feature (user selection/navigation of content to be provided to a content device from a networked system/server, Col. 5, Lines 49-54, where requests include "submitted" user customization features/preferences (e.g., compression percentage), Col. 8, Lines 52-62, Col. 16, Lines 17-40, Col. 24, Lines 27-35 and Col. 34, Lines 55-67; see also client devices running applications for content access, Fig. 1, Elements 110 and 102; note that content includes audio content such as podcasts, Col. 12, Lines 24-30; “news articles,” Col. 12, Line 57- Col. 13, Line 3; the interactive interfaces allowing for dynamic customization, Col. 19, Lines 61-64 and Col. 20, Lines 29-33, including a plurality of different inputs corresponding to different candidate features that enables concurrent selection of such multiple features (e.g., zoom, abstraction, and vocabulary among others), Col. 24, Lines 26-67; Col. 28, Line 39- Col. 30, Line 23; and Col. 12, Lines 24-51);
generating a summary of the article based upon the podcast customizing feature (generating a summary based upon the dynamically selected abstraction parameters/preferences, Col. 13, Lines 10-18; Col. 14, Lines 37-42; Col. 18, Lines 25-39; Col. 26, Lines 16-17 and 55-60; see also Col. 24, Lines 34-35- "User preferences may directly inform desired summarization behavior");
generating the podcast to comprise an auditory representation of the summary (Col. 12, Lines 40-51- "system may generate multimedia summaries optimized for different modalities, such as spoken audio summaries;" Col. 11, Line 27- "text-to-speech converted summaries;" See also Col. 48, Lines 41-44 and 53-54; note that content includes audio content such as podcasts, Col. 12, Lines 24-30); and
providing the podcast to the client device (customized summary is returned to the user, Col. 26, Lines 55-60; client device access of content at Col 4, Line 58- Col. 5, Line 12).
With respect to Claim 12, Gardner further discloses:
The computing device of claim 11, the operations comprising: providing, for display on the client device, a content interface providing the first content item and the podcast customization interface (user interface for content navigation and customization parameter selection, Col. 5, Lines 49-54; Col. 8, Lines 52-63; Col. 13, Lines 9-18; and Col. 19, Lines 32-44), wherein: the podcast customization interface comprises a first selectable input associated with generating the podcast; and the request is received in response to a selection of the first selectable input (user selection/navigation of content to be provided to a content device from a networked system/server, Col. 5, Lines 49-54, where selectable requests include "submitted" user customization features/preferences (e.g., compression percentage), Col. 8, Lines 52-62, Col. 16, Lines 17-40, Col. 24, Lines 27-35 and Col. 34, Lines 55-67; see also client devices running applications for content access, Fig. 1, Elements 110 and 102; note that content includes audio content such as podcasts, Col. 12, Lines 24-30.
With respect to Claim 14, Gardner further discloses:
The computing device of claim 11, wherein: the request comprises one or more podcast customizing features comprising a target length of the podcast (user settings for controlling the length of content/summary length, Col. 21, Lines 52-26; Col. 22, Lines 27-31; Col. 24, Lines 28-30 and 55-59; note that content includes audio content such as podcasts, Col. 12, Lines 24-30).
With respect to Claim 15, Gardner further discloses:
The computing device of claim 14, comprising: determining a target summary length based upon the target length (user preferences "guide" customization/summarization including degrees of abstraction and summary length, Col. 21, Lines 52-26; Col. 22, Lines 27-31; Col. 24, Lines 28-30 and 55-59); and submitting an indication of the target summary length to a language model, wherein generating the summary is performed using the language model based upon the target summary length (abstraction targets are submitted to a large language model (LLM) to generate the summary that hits such targets with "desired...length," Col. 13, Lines 19-61; Col. 17, Lines 7-12; Fig. 2, Element 230).
Claim 16 recites an alternate embodiment for practicing the functionality of claim 11 as processor-executable instructions stored on a non-transitory machine-readable medium, and thus, is rejected under similar rationale. It should be noted that the language of claim 16 differs slightly from claim 11 in that the requested first podcast is the summary of the second podcast. Note that Gardner teaches that a requested (via a user interface) different/second content item (i.e., the claimed first podcast) includes a subset "representing the first content item" (i.e., the claimed second podcast) omitting or simplifying certain elements (Col. 13, Lines 9-18; Col. 13, Line 43- Col. 14, Line 11; Col. 13, Lines 27-36). Gardner also teaches method implementation as a computer program stored on a non-transitory machine-readable medium (Col. 66, Lines 9-42).
With respect to Claim 17, Gardner further discloses:
The non-transitory machine-readable medium of claim 16, the operations comprising: converting audio of the second podcast to a transcript, wherein generating the summary of the second podcast is performed using the transcript (Col. 12, Lines 24-30- "automated speech recognition may first be used to transcribe the audio to text. The resulting text transcript may then [be] summarized using the system's text summarization capabilities").
Claim 18 contains subject matter similar to Claim 14, and thus, is rejected under similar rationale.
Claim 19 recites subject matter similar to Claim 15, and thus, is rejected under similar rationale.
With respect to Claim 20, Gardner further discloses:
The non-transitory machine readable medium of claim 16, wherein: generating the first podcast comprises converting the summary to the auditory representation of the summary using a text-to-speech converter (Col. 12, Lines 40-51- "system may generate multimedia summaries optimized for different modalities, such as spoken audio summaries;" Col. 11, Line 27- "text-to-speech converted summaries").
Claims 1-10 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Gardner, et al. (U.S. Patent: 12,008,332) in view of Basu, et al. (U.S. PG Publication: 2008/0300872 A1).
With respect to Claim 1, Gardner discloses:
A method, comprising:
receiving, via the podcast customization interface ("user interfaces to control the depth of summarization" for audio podcast generation, Col. 8, Lines 52-63; Col. 12, Lines 24-46,Col. 13, Lines 9-18; Col. 19, Lines 32-64), a request to provide a podcast to a client device, wherein the request is indicative of one or more podcast customizing features comprising the first podcast customizing feature (user selection/navigation of content to be provided to a content device from a networked system/server, Col. 5, Lines 49-54, where requests include "submitted" user customization features/preferences submitted through the UI (e.g., compression percentage), Col. 8, Lines 52-63, Col. 16, Lines 17-40, Col. 24, Lines 27-35 and Col. 34, Lines 55-67; see also client devices running applications for content access, Fig. 1, Elements 110 and 102; note that content includes audio content such as podcasts, Col. 12, Lines 24-30);
determining, based upon the request, a set of content items (identifying a first set of content items based upon, e.g., user navigation, Col. 12, Line 57- Col. 13, Line 3 and Col. 5, Lines 49-54);
generating a summary of the set of content items based upon at least one of the podcast customizing features comprising the first podcast customizing features (generating a summary based upon the user abstraction parameters/preferences, Col. 13, Lines 10-18; Col. 14, Lines 37-42; Col. 18, Lines 25-39; Col. 26, Lines 16-17 and 55-60; see also Col. 24, Lines 34-35- "User preferences may directly inform desired summarization behavior");
generating the podcast to comprise an auditory representation of the summary (Col. 12, Lines 40-51- "system may generate multimedia summaries optimized for different modalities, such as spoken audio summaries;" Col. 11, Line 27- "text-to-speech converted summaries;" See also Col. 48, Lines 41-44 and 53-54; note that content includes audio content such as podcasts, Col. 12, Lines 24-30); and
providing the podcast to the client device (customized summary is returned to the user, Col. 26, Lines 55-60; client device access of content at Col 4, Line 58- Col. 5, Line 12).
Although Gardner teaches the generation of an audio podcast customization interface for inputting user levels of abstraction and preferences that inform summarization behavior in generated “text-to-speech converted summaries,” Gardner does not teach “generating a podcast customization interface associated with a first content item, wherein the generating comprises generating a first interface, for submitting an indication of a first podcast customizing feature, based upon an analysis of the first content item wherein the first interface (i) comprising a plurality of inputs each corresponding to a different candidate feature identified based upon the analysis of the first content item and (ii) enabling a user of the podcast customization interface to concurrently select multiple candidate features identified based upon the analysis of the first content item in association with the first podcast customizing feature.” Basu, however, teaches a browsing interface for customized audio content playback via summarization that dynamically generates adjustable portions of content by analyzing the input content (e.g., with speech recognition along with keyword extraction) (Paragraphs 0029, 0032, 0038-0039, 0045, and 0047). Moreover, Basu’s interface generated based upon content analysis allows for the display of multiple input features and enables their concurrent selection (audio summary playback/rendering based upon a number of concurrently selectable factors populated in an interface and based upon speech analysis/classification of input content such as topic, plural/groups of identified keywords, and speaker turn, Paragraphs 0054, 0057-0058, 0062, 0067, 0070, and 0073).
Gardner and Basu are analogous art because they are from a similar field of endeavor in automated audio content summarization generation. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to include dynamically generated portions of a user interface based upon keywords extracted from content as taught by Basu in the podcast customization interface for entering user abstraction levels and preferences as taught by Gardner to provide a predictable result of allowing a user to listen to specific condensed groups of content associated with regions of user interest present in the content (Basu, Paragraph 0059).
With respect to Claim 2, Gardner further discloses:
The method of claim 1, comprising: providing, for display on the client device, a content interface providing the first content item and the podcast customization interface (user interface for content navigation and customization parameter selection, Col. 5, Lines 49-54; Col. 8, Lines 52-63; Col. 13, Lines 9-18; and Col. 19, Lines 32-44), wherein: the set of content items comprise the first content item (the first content item contains "multiple sub-content items," Col. 12, Line 57- Col. 13, Line 3).
With respect to Claim 3, Gardner further discloses:
The method of claim 1, wherein: the podcast customization interface further comprises a second interface for submitting an indication of a second podcast customizing feature comprising at least one of a first target length (summary length, Col. 24, Lines 30 and 58-59), a first audience competency level (expertise/proficiency levels, Col. 24, Line 31 and Col. 28, Lines 24-27), a first level of detail or a first podcast mode (level of detail/zoom mode, Col. 12, Lines 24-30 and Col. 27, Lines 13-32); and the request is indicative of the second podcast customizing feature (the various secondary inputs are provided via user preference interface elements, Col. 8, Lines 52-63, Col. 16, Lines 17-40, Col. 24, Lines 27-35 and Col. 34, Lines 55-67).
With respect to Claim 4, Basu further discloses:
The method of claim 2, wherein: the analysis of the first content item determines that two or more entities (e.g., a keyword and speaker; multiple keywords) associated with the first podcast customizing feature are referred to in the first content item (keyword-based customization wherein analysis determines a plurality of keywords, speakers, turns, topics, etc. present in the first content item, Paragraphs 0027, 0029, 0032, 0038-0039, 0045, 0047, 0054, 0056-0058, 0062, 0067, 0070, and 0073); and
the plurality of inputs, of the first interface, comprises (i) a first input corresponding to a first candidate feature comprising a first entity of the two or more entities and (ii) a second input corresponding to a second candidate feature comprising a second entity of the two or more entities (input interface for selection of first and second entities such as plural/groups of identified keywords and/or speaker, Paragraphs 0054, 0057-0058, 0062, 0067, 0070, and 0073).
With respect to Claim 5, Gardner further discloses:
The method of claim 1, wherein: the one or more podcast customizing features comprise a target length of the podcast (user settings for controlling the length of content/summary length, Col. 21, Lines 52-26; Col. 22, Lines 27-31; Col. 24, Lines 28-30 and 55-59; note that content includes audio content such as podcasts, Col. 12, Lines 24-30).
With respect to Claim 6, Gardner further discloses:
The method of claim 5, comprising: determining a target summary length based upon the target length (user preferences "guide" customization/summarization including degrees of abstraction and summary length, Col. 21, Lines 52-26; Col. 22, Lines 27-31; Col. 24, Lines 28-30 and 55-59); and submitting an indication of the target summary length to a language model, wherein generating the summary is performed using the language model based upon the target summary length (abstraction targets are submitted to a large language model (LLM) to generate the summary that hits such targets with "desired...length," Col. 13, Lines 19-61; Col. 17, Lines 7-12; Fig. 2, Element 230).
With respect to Claim 7, Gardner further discloses:
The method of claim 1, wherein: the one or more podcast customizing features comprise an entity of interest associated with the podcast (keyword of interest used to retrieve audio content, Col. 49-54); determining the set of content items comprises: analyzing a database of content items to identify the first content item comprising first information associated with the entity of interest (database of content is retried including audio information content according to matching attributes stored as metadata, Col. 49-54); and including the first content item in the set of content items (identifying the first content item, Col. 12, Line 57- Col. 13, Line); and generating the summary of the set of content items comprises including, in the summary, a set of text indicative of at least some of the first information associated with the entity of interest (the summary includes a subset "representing the first content item" omitting or simplifying certain elements thereby including at least some of the audio information that was retrieved pertaining to the keyword/entity of interest wherein the output may include text, Col. 13, Lines 9-18; Col. 13, Line 43- Col. 14, Line 11; Col. 13, Lines 27-36 discussing summarization focusing on content themes).
With respect to Claim 8, Gardner further discloses:
The method of claim 1, wherein: generating the podcast comprises converting the summary to the auditory representation of the summary using a text-to-speech converter (Col. 12, Lines 40-51- "system may generate multimedia summaries optimized for different modalities, such as spoken audio summaries;" Col. 11, Line 27- "text-to-speech converted summaries").
With respect to Claim 9, Gardner further discloses:
The method of claim 1, wherein: the one or more podcast customizing features comprise a level of detail of the podcast (level of detail/abstraction that can include lessening or expanding content, Col. 13, Lines 9-18; Col. 17, Lines 28-49; Col. 22, Lines 1-12; note that content includes audio content such as podcasts, Col. 12, Lines 24-30).
With respect to Claim 10, Gardner further discloses:
The method of claim 1, wherein: the one or more podcast customizing features comprise an audience competency level associated with the podcast (content vocabulary according to “expertise levels,” Col. 14, Lines 12-23; Col. 16, Lines 31-33; Col. 24, Lines 30-31; Col. 28, Lines 24-27; Col. 45, Lines 15-20).
With respect to Claim 13, Gardner teaches the device for podcast customization and summarization as applied to Claim 11. Gardner fails to teach; however, Basu discloses that the dynamic interface is generated based upon an analysis of a first content item (a browsing interface for customized audio content playback via summarization that dynamically generates adjustable portions of content by analyzing the input content (e.g., with speech recognition along with keyword extraction) (Paragraphs 0029, 0032, 0038-0039, 0045, and 0047)).
Gardner and Basu are analogous art because they are from a similar field of endeavor in automated audio content summarization generation. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date to include dynamically generated portions of a user interface based upon keywords extracted from content as taught by Basu in the podcast customization interface for entering user abstraction levels and preferences as taught by Gardner to provide a predictable result of allowing a user to listen to specific portions of content associated with a keyword of interest present in the content (Basu, Paragraph 0059).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Paglia, et al. (U.S. PG Publication: 2023/0289382 A1)- teaches a media file transcript analysis to detect topics, entities, speakers, sections, etc. to enable dynamic playback across "terms and speakers" (Abstract).
Laban, et al. ("NewsPod: Automatic and Interactive News Podcasts," March 2022)- teaches a podcast summarization tool that performs content analysis and generates an interface including a series of selected topics (e.g., concurrent selection of 5 topical segments to generate a personalized podcast) and length that enables podcast generation on demand (Sections 5.1-5.2, Pages 694-695).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES S WOZNIAK whose telephone number is (571)272-7632. The examiner can normally be reached 7-3, off alternate Fridays.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Flanders can be reached at (571)272-7516. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JAMES S. WOZNIAK
Primary Examiner
Art Unit 2655
/JAMES S WOZNIAK/Primary Examiner, Art Unit 2655
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