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 .
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.
(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.
Claim(s) 1-4, 7-11, 13-17, 20 is/are rejected under 35 U.S.C. 102(a)(1) and 35 U.S.C. 102 (a)(2) as being anticipated by Vepa et al. (US 20230394244 A1).
Regarding claim 1, Vepa discloses:
A method comprising:
identifying, via at least one processor, a plurality of portions of one or more communication sessions between users, (An interaction event within a recorded audio stream is detected. In various embodiments, the recorded audio stream includes a conversation between at least two participants/speakers and where each participant has a corresponding role in the conversation [0019]) wherein the plurality of portions includes at least one portion with silence and at least one portion with crosstalk (Examples of types of interaction events include speech, silence, music, speech-over-music, background speech, noise, and dial-tone. Which one or more types of interaction events that interaction event detection server 108 is to detect within an audio stream can be configurable/predetermined prior to detection [0022] The examiner considers the broadest reasonable interpretation of the prior art including interaction events such as speech over music and background speech to be similar and not limiting);
classifying, via a machine learning classifier of the at least one processor, each portion with silence as one of a positive user experience and a negative user experience (Other types of predefined classifications include whether the detected interaction was associated with a positive sentiment, a negative sentiment by a corresponding speaker (e.g., a customer) [0023]) based on sections of a corresponding communication session preceding and subsequent the silence (For the purpose of illustration, in several examples used herein, the type of interaction event that is detected and subsequently classified by interaction event detection server 108 is silence [0022] In some embodiments, the contextual text relative to the detected interaction event may include a first set of words that precedes the interaction event in the text transcription and a second set of words that follows the interaction event in the text transcription [0023]);
classifying, via the machine learning classifier of the at least one processor, each portion with crosstalk as one of the positive user experience and the negative user experience (Other types of predefined classifications include whether the detected interaction was associated with a positive sentiment, a negative sentiment by a corresponding speaker (e.g., a customer) [0023]) based on the crosstalk and sections in a corresponding communication session (Examples of types of interaction events include speech, silence, music, speech-over-music, background speech, noise, and dial-tone. Which one or more types of interaction events that interaction event detection server 108 is to detect within an audio stream can be configurable/predetermined prior to detection [0022]) preceding and subsequent the crosstalk (In some embodiments, the contextual text relative to the detected interaction event may include a first set of words that precedes the interaction event in the text transcription and a second set of words that follows the interaction event in the text transcription [0023]); and
conducting, via the at least one processor, a communication session with at least one participant selected (when an agent has been determined to be the causer of one or more interaction events (e.g., including a silent segment that exceeds a time limit), the supervisor is notified of such events and is provided the opportunity to intervene [0091]) based on classifications of the silence and crosstalk (interaction event detection server 108 is configured to generate, for the detected interaction event, a classification comprising whether a detected interaction event is intentional/expected and also, which of the participants/speakers had caused the detected interaction event [0023]);
Regarding claim 2, Vepa discloses:
The method of claim 1, wherein the machine learning classifier includes:
a first large language model to classify each portion (Interaction event detection server 108 is configured to detect audio segment(s) of a predetermined type of interaction event within an audio stream based on inputting portions of the audio stream into a machine learning mode [0022]) with silence (Examples of types of interaction events include speech, silence, music, speech-over-music, background speech, noise, and dial-tone. Which one or more types of interaction events that interaction event detection server 108 is to detect within an audio stream can be configurable/predetermined prior to detection [0022]); and
a second large language model to classify each portion with crosstalk (to be programmatically detected and classified (e.g., using a cascade of two different machine learning models) within a recorded audio stream [0026]);
Regarding claim 3, Vepa discloses:
The method of claim 1, wherein classifying each portion with silence comprises:
classifying each portion with silence based on the sections preceding and subsequent the silence (the contextual text relative to the detected interaction event may include a first set of words that precedes the interaction event in the text transcription and a second set of words that follows the interaction event in the text transcription [0023]) indicating resolution of an issue, receipt of appropriate information for the issue, and/or an expectedness of the silence (interaction event detection server 108 is configured to generate, for the detected interaction event, a classification comprising whether a detected interaction event is intentional/expected [0023]);
Regarding claim 4, Vepa discloses:
The method of claim 1, wherein classifying each portion with crosstalk comprises:
classifying each portion with crosstalk based on the crosstalk and/or the sections preceding and subsequent the crosstalk (the contextual text relative to the detected interaction event may include a first set of words that precedes the interaction event in the text transcription and a second set of words that follows the interaction event in the text transcription [0023]) indicating an agreement or affirmation by the users (or there is a mutual understanding between the participants about a silent segment [0072] Which one or more types of interaction events that interaction event detection server 108 is to detect within an audio stream can be configurable/predetermined prior to detection [0022]);
Regarding claim 7, Vepa discloses
The method of claim 1, wherein the one or more communication sessions between the users include an online meeting (a specific example, where a recorded audio source server comprises a server located in a contact center, the participants in a recorded audio stream include a customer service agent and a customer and where the agent is assisting the customer in resolving an issue [0021]);
Claim 8 contains similar limitations to claim 1 and is therefore rejected for the same reasons.
Claim 9 contains similar limitations to claim 3 and is therefore rejected for the same reasons.
Claim 10 contains similar limitations to claim 4 and is therefore rejected for the same reasons.
Claim 11 contains similar limitations to claim 5 and is therefore rejected for the same reasons.
Claim 13 contains similar limitations to claim 7 and is therefore rejected for the same reasons.
Claim 14 contains similar limitations to claim 1 and is therefore rejected for the same reasons.
Claim 15 contains similar limitations to claim 2 and is therefore rejected for the same reasons.
Claim 16 contains similar limitations to claim 3 and is therefore rejected for the same reasons.
Claim 17 contains similar limitations to claim 4 and is therefore rejected for the same reasons.
Claim 20 contains similar limitations to claim 7 and is therefore rejected for the same reasons.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 5-6, 12, 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vepa et al. (US 20230394244 A1) in view of Yee et al. (US 20250023983 A1).
Regarding claim 5, in addition to the elements stated above regarding claim 1, Vepa in view of Yee discloses:
The method of claim 1, wherein the users include an agent of a contact center, and the method further comprises:
generating, via the at least one processor, [assessment] for the agent based on classifications for the silence and crosstalk (In some embodiments, interaction event detection server 108 is configured to determine one or more other types of predefined classifications associated with the detected interaction event. Other types of predefined classifications include whether the detected interaction was associated with a positive sentiment, a negative sentiment by a corresponding speaker [Vepa 0023]);
Vepa discloses the claimed contact center agent and generation of classifications of interaction events, which can be positive and/or negative classifications. Vepa does not expressly disclose generating one or more scores for the agent based on the classifications for silence and crosstalk.
However, Yee discloses:
generating, via the at least one processor, one or more scores (automatically determining, by the at least one processor, based on a sentiment analysis of the at least one key term, a confidence positivity score [Yee 0091]);
Vepa and Yee are considered analogous to the claimed invention because both are directed at analyzing user interactions. Therefore, it would have been obvious to apply Yee’s scoring technique to Vepa’s classified interaction information to provide a quantitative measure of the classified user interaction for evaluating agent performance. It would have predictably improved the interaction information for the agent by providing a score to add as additional information.
Regarding claim 6, in addition to the elements stated above regarding claim 1 and 5, Vepa in view of Yee discloses:
The method of claim 5, further comprising:
routing, via the at least one processor, a communication to a corresponding agent of the contact center (To that end, the user interfaces shown in FIGS. 11A-11D can provide real-time (live) feedback to the agent to inform him or her of the current state [0085 of Vepa]) based on the one or more scores (automatically determining, by the at least one processor, based on a sentiment analysis of the at least one key term, a confidence positivity score [Yee 0091] In some embodiments, the confidence positivity score may become a threshold of confidence that the user is comfortable with discussing the identified personal information [Yee 0023]);
Claim 12 contains similar limitations to claims 5-6 and is therefore rejected for the same reasons.
Claim 18 contains similar limitations to claim 5 and is therefore rejected for the same reasons.
Claim 19 contains similar limitations to claim 6 and is therefore rejected for the same reasons.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kyle Espinas whose telephone number is (571)270-0596. The examiner can normally be reached Monday Friday, 8 a.m. 5 p.m. ET..
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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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/Kylenino Espinas/
Patent Examiner
Art Unit 2655
8/11/2026
/ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655
Prosecution Insights