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 .
This action is in response to the application filed on 18 September 2024.
Claims 1-20 are under examination.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 18 September 2024 and 09 February 2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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)(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 1, 3-17, 19 and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kwatra et al. (US Publication 2020/0052920).
With respect to claims 1 and 20, Kwatra teaches A method for termination of a call involving multiple different call devices, the method comprising:
monitoring an established call between multiple call devices to detect an audible level that is at or below a pre-selected silence threshold for a pre-selected silence time period to detect a silence event to trigger analysis of the detected silence event; (A timer may be used to monitor and maintain a duration of the conference call (e.g., a start time and an end time) for one or more scheduled conference calls/events. Upon expiration of a predetermined amount of time such as, a period of detected silence, the connection/disconnection component 420 may determine users 480 and/or 485 have failed to respond and may also determine a physical or virtual presence and/or a physical or virtual absence of the users 480 and/or 485, Paragraph 75)
triggering analysis of the detected silence event so that an analysis of (a) a transcription of a portion of the call, (b) metadata information related to the call, (c) a sound pattern analysis of the call during the pre-selected silence time period, and/or (d) a duration of time in which the audible level is at or below the pre-selected silence threshold is performed to generate analysis results from the triggered analysis; (parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, Paragraph 76)
evaluating the analysis results to determine whether the call is terminated; (Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76) and
terminating the call based on the evaluated analysis results indicating that the call is terminated and releasing resources assigned to the call based on the evaluated analysis results indicating that the call is terminated. (The connection/disconnection component 420 may automatically terminate the communication connection according to an identified user of the one or more users (e.g., users 480 and/or 485) leaving the conference call session. The connection/disconnection component 420 may also automatically terminate the communication connection after a time period of silence of the conference call session has exceeded a threshold, identification of one or more keywords, voice recognition data of the one or more users identified during the conference call, or a combination thereof, paragraph 72)
With respect to claims 3, Kwatra teaches comprising: analyzing the transcription of a portion of the call and the metadata information related to the call to generate a context analysis result. (the device identification and tracking component 412 and/or the user ID and tracking component 414 may monitor the schedule of the one or more users (e.g., users 480 or 485), each of the ADLs of the user, and the one or more contextual factors using a machine learning operation of machine learning component 418, one or more IoT computing devices (e.g., device 460/IoT device 470), or a combination thereof, Paragraph 67)
With respect to claims 4, Kwatra teaches comprising: analyzing the sound pattern analysis of the call during the pre-selected silence time period, and/or the duration of time in which the audible level is at or below the pre-selected silence threshold is performed to generate the analysis results. (The connection/disconnection component 420 may automatically terminate the communication connection according to an identified user of the one or more users (e.g., users 480 and/or 485) leaving the conference call session. The connection/disconnection component 420 may also automatically terminate the communication connection after a time period of silence of the conference call session has exceeded a threshold, identification of one or more keywords, voice recognition data of the one or more users identified during the conference call, or a combination thereof, paragraph 72)
With respect to claims 5, Kwatra teaches wherein the sound pattern analysis of the call during the pre-selected silence time period is analyzed and duration of time in which the audible level is at or below the pre-selected silence threshold is analyzed to generate the analysis results from the triggered analysis. (The connection/disconnection component 420 may automatically terminate the communication connection according to an identified user of the one or more users (e.g., users 480 and/or 485) leaving the conference call session. The connection/disconnection component 420 may also automatically terminate the communication connection after a time period of silence of the conference call session has exceeded a threshold, identification of one or more keywords, voice recognition data of the one or more users identified during the conference call, or a combination thereof, paragraph 72)
With respect to claims 6, Kwatra teaches wherein a communication device performs the monitoring, the triggering of the analysis, the evaluating of the analysis results, and the terminating of the call, the communication device having a processor connected to a non-transitory memory. (where the instructions are included on at least one computer readable medium or on a non-transitory machine-readable storage medium, paragraph 80)
With respect to claims 7, Kwatra teaches wherein the evaluating of the analysis results to determine whether the call is terminated includes utilization of a predetermined Random Forest model. (the machine learning component 418 may apply one or more heuristics and machine learning based models using a wide variety of combinations of methods, such as supervised learning, unsupervised learning, temporal difference learning, reinforcement learning and so forth. Some non-limiting examples of supervised learning which may be used with the present technology include AODE (averaged one-dependence estimators), artificial neural networks, Bayesian statistics, naive Bayes classifier, Bayesian network, case-based reasoning, decision trees, inductive logic programming, Gaussian process regression, gene expression programming, group method of data handling (GMDH), learning automata, learning vector quantization, minimum message length (decision trees, decision graphs, etc.), lazy learning, instance-based learning, nearest neighbor algorithm, analogical modeling, probably approximately correct (PAC) learning, ripple down rules, a knowledge acquisition methodology, symbolic machine learning algorithms, sub symbolic machine learning algorithms, support vector machines, random forests, ensembles of classifiers, bootstrap aggregating (bagging), boosting (meta-algorithm), ordinal classification, regression analysis, information fuzzy networks (IFN), statistical classification, linear classifiers, fisher's linear discriminant, logistic regression, paragraph 79)
With respect to claims 8 and 19, Kwatra teaches wherein the evaluating of the analysis results includes: determining a raw score for a context analysis based on the transcription of the portion of the call and the metadata information related to the call, determining a raw score for the sound pattern analysis of the call during the pre-selected silence time period, and/or determining a raw score for the duration of time in which the audible level is at or below the pre-selected silence threshold. (Parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76)
With respect to claims 9, Kwatra teaches wherein the evaluating of the analysis results includes: determining a cumulative score based on the raw score for a context analysis, the raw score for the sound pattern analysis and/or the raw score for the duration of time in which the audible level is at or below the pre-selected silence threshold. (Parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76)
With respect to claims 10, Kwatra teaches wherein the evaluated analysis results indicate that the call is terminated because the cumulative score is over a pre-selected threshold value for the cumulative score and the raw score for the context analysis is at or over a pre-selected threshold value for the raw score for the context analysis. (Parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76)
With respect to claims 11, Kwatra teaches wherein the evaluated analysis results indicate that the call is terminated because the cumulative score is over a pre-selected threshold value for the cumulative score and the raw score for the context analysis is at or over a pre-selected threshold value for the raw score for the context analysis and the raw score for the duration of time in which the audible level is at or below the pre-selected silence threshold is at or over a pre-selected threshold value for the raw score for the duration of time in which the audible level is at or below the pre-selected silence threshold. (Parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76)
With respect to claims 12, Kwatra teaches wherein the evaluated analysis results indicate that the call is terminated because the raw score for the context analysis is at or over a pre-selected threshold value for the raw score for the context analysis and the raw score for the duration of time in which the audible level is at or below the pre-selected silence threshold is at or over a pre-selected threshold value for the raw score for the duration of time in which the audible level is at or below the pre-selected silence threshold. (Parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76)
With respect to claims 13, Kwatra teaches wherein the evaluated analysis results indicate that the call is terminated because the raw score for the context analysis is at or over a pre-selected threshold value for the raw score for the context analysis. (Parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76)
With respect to claims 14, Kwatra teaches comprising: updating parameters utilized in the evaluating of the analysis results and/or the parameters utilized to generate the analysis results based on evaluation of empirical performance in which different calls were terminated (The machine learning component 418 may learn, identity, behavior, activity, contextual factors, and/or the parameters. Also, machine learning component 418 may identity the presence or absence of a user (e.g., user 480 and/or 485). In one aspect, the machine learning component 418 may extract one or more features for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Additionally, the machine learning component 418 may learn a call is scheduled on a calendar of a user such as, for example, uses 480 and/or 485. The machine learning component 418 may then issue a notification to user 485, which may state “A conference call is now starting. No other priority events are detected. You are now placed into the call, paragraph 77)
With respect to claims 15, Kwatra teaches wherein the metadata information includes data indicating a current number of call devices remaining in the call and a maximum number of the call devices included in the call. (may determine 1) a number of users that have joined or disconnected from the conference call session, 2) a priority level of one or more events related to the user profile, the schedule of the one or more users, 3) one or more ADLs of each user, the one or more contextual factors associated with each of the user, or a combination thereof for cognitively initiating the communication connection for the conference call session., paragraph 87)
With respect to claims 16, Kwatra teaches wherein the analysis of the metadata information related to the call includes an analysis of a ratio of the current number of call devices remaining in the call and the maximum number of the call devices included in the call. (may determine 1) a number of users that have joined or disconnected from the conference call session, 2) a priority level of one or more events related to the user profile, the schedule of the one or more users, 3) one or more ADLs of each user, the one or more contextual factors associated with each of the user, or a combination thereof for cognitively initiating the communication connection for the conference call session., paragraph 87)
With respect to claim 17, Kwatra teaches A telecommunication apparatus comprising: a network element having a processor connected to a non-transitory computer readable medium, the network element being connectable to different call devices for establishment of at least one call between the different call devices; (processor, figure 1)
the network element configured to monitor at least one established call between multiple different call devices of the different call devices to detect an audible level that is at or below a pre-selected silence threshold for a pre-selected silence time period to detect a silence event to trigger analysis of the detected silence event; (A timer may be used to monitor and maintain a duration of the conference call (e.g., a start time and an end time) for one or more scheduled conference calls/events. Upon expiration of a predetermined amount of time such as, a period of detected silence, the connection/disconnection component 420 may determine users 480 and/or 485 have failed to respond and may also determine a physical or virtual presence and/or a physical or virtual absence of the users 480 and/or 485, Paragraph 75)
the network element configured to trigger analysis of the detected silence event so that an analysis of (a) a transcription of a portion of the call, (b) metadata information related to the call, (c) a sound pattern analysis of the call during the pre-selected silence time period, and/or (d) a duration of time in which the audible level is at or below the pre-selected silence threshold is performed to generate analysis results from the triggered analysis; (parameters involved for determining the time when to terminate, disconnect, and/or hang up the conversation may include one or more of the following. The parameters may include checking a duration of a call from the meeting details. Also, a parameter may include a determining if users (e.g., users 480 and/or 485) are still discussing the conference call. In one aspect, a determine may be performed to determine if the users are still active on the call and communicating on the conference call such as, for example, using on natural language processing (“NLP”) keyword extraction and feature extraction (e.g., Mel Frequency Cepstral Coefficients “MFCC”) for feature extraction of the speech and NLP for keyword extraction to determine the relevance of the conversation after the scheduled time of the conference call has completed/expired. Moreover, the parameters may include a threshold of silence (e.g., period of silence) after the scheduled conference call duration has ended or scheduled to be over such as, for example, 2 minutes after the call was scheduled to end. Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, Paragraph 76)
the network element configured to evaluate the analysis results to determine whether the call is terminated; (Once these parameters are evaluated and satisfied to exceed a specific threshold factor, the connection/disconnection component 420 may disconnect and terminated, paragraph 76) and
the network element configured to terminate the at least one established call based on the evaluated analysis results indicating that the call is terminated and release resources assigned to the at least one established call based on the evaluated analysis results indicating that the call is terminated. (The connection/disconnection component 420 may automatically terminate the communication connection according to an identified user of the one or more users (e.g., users 480 and/or 485) leaving the conference call session. The connection/disconnection component 420 may also automatically terminate the communication connection after a time period of silence of the conference call session has exceeded a threshold, identification of one or more keywords, voice recognition data of the one or more users identified during the conference call, or a combination thereof, paragraph 72)
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness
Claims 2 and 18 are rejected under 35 U.S.C. 103(a) as being unpatentable over Kwatra et al. (US Publication 2020/0052920) in view of Chatterjee et al. (US Publication 2017/0064075).
With respect to claims 2 and 18, Kwatra doesn’t teach wherein the releasing of the resources assigned to the call includes releasing recorder services assigned to the call or session initiation protocol (SIP) recorder services assigned to the call.
Chatterjee teaches wherein the releasing of the resources assigned to the call includes releasing recorder services assigned to the call or session initiation protocol (SIP) recorder services assigned to the call. (The processes of determining that the media recorder 121A is unable to continue recording the media stream in steps 208, 212, 214, and 216 are described using SIP messages. However, the messages of steps 208, 212, 214, and 216 may be implemented using any protocol, such as Hyper Text Transport Protocol (HTTP)/REpresentational State Transfer (REST) protocol, proprietary protocols, UDP/IP, TCP/IP, and/or the like, Paragraph 34)
Thus it would have been obvious to one of ordinary skill in the art at the time of the invention to implement system of Kwatra with the releasing of the resources assigned to the call includes releasing recorder services assigned to the call or session initiation protocol (SIP) recorder services assigned to the call as taught by Chatterjee. The motivation for combining Kwatra and Chatterjee is to be able to efficiently manage a call recording.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Etayo et al. (US Patent 12,664,997) discloses detect discrete audio events in the audio signal, calculate a quality score for the audio signal, the quality score based on a running average over a time period, wherein the running average is based on a number of the discrete audio events of the audio signal detected during the time period and disruption scores associated with the discrete audio events, cause the display device to display the quality score, and cause the display device to display information about the discrete audio events having disruption scores exceeding a threshold.
Mammen et al. (US patent 10,891,940) discloses each potential instance of the target word is audibly reviewed and validated by a user. After a determination of the correctness of each potential instance's classification, a different confidence score threshold value can be used to produce an updated set of classification results without requiring the user to revalidate the results. By using a variety of confidence score threshold values to produce various sets of classification results, an optimized confidence threshold setting can be determined for the identified target word based on minimizing errors in the various results. This value can then be applied for future analysis of the target word in an audio source.
Any inquiry concerning this communication from the examiner should be directed to ABDULLAHI AHMED whose telephone number is (571) 270-3652. The examiner can normally be reached on M-F 8:00AM-4:30PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Khalid Kassim can be reached on 571-270-3370. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ABDULLAHI AHMED/Examiner, Art Unit 2475
Prosecution Insights