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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on July 23, 2026, has been entered.
Response to Arguments
Applicant's arguments, filed July 23, 2026, with respect to the rejections of claims 1, 3 – 9, 11 – 13, 15 – 20 and 22 – 24 under 35 U.S.C. 103 have been fully considered but they are not persuasive.
On page 8 of Applicant’s response, Applicant argues “No combination of Akkiraju, Alexander, and Bhatt describes or suggests a computer system as recited in amended Claim 1. More specifically, no combination of Akkiraju, Alexander, and Bhatt describes or suggests at least one processor and/or transceiver being programmed to "generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time, and (ii) the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time."”.
However, Akkiraju et al. (US Patent No. 10,037,768), hereinafter Akkiraju, recites, in column 8, line 64 - column 9, line 8, "In an embodiment, conversation analysis program 137 stores conversation (step 212). In other words, conversation analysis program 137 stores the annotated conversation and the results from best practice pattern analyzer 135 to a memory. In an embodiment, the annotated conversation and the results from best practice pattern analyzer 135 for the analysis of the on-going conversation are stored to a database found in a memory (not shown in FIG. 1) on server device 130. For example, the entire annotated and scored conversation between customer “Jill” and company representative “Dan”, and any recommendations made to “Dan” for proper responses to “Jill” is stored to a memory.", and recites, in column 9, lines 21-29, "In an embodiment, conversation analysis program 137 retrieves conversation (step 302). In other words, conversation analysis program 137 retrieves a plurality of annotated and scored conversations from a database stored to a memory (not shown in FIG. 1) on server device 130. In an embodiment, conversation analysis program 137 retrieves the plurality of conversations from a pre-defined time frame (e.g., from the last week, from the last two weeks, from the last month, etc.).", disclosing generating a report including the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time, where storing and retrieving a plurality of scored conversations in a database reads on generating a report including the respective score determined for each conversation of the plurality of completed conversations, under the broadest reasonable interpretation of “report”, and retrieving the plurality of scored conversations from a pre-defined time frame reads on the report including the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time.
Alexander et al. (US Patent Application Publication No. 2024/0193373), hereinafter Alexander, recites, in paragraph 0073, lines 1-40, "In one or more implementations, the conversation mapping process 500 is supported or otherwise implemented by an application platform at a server of a database system (e.g., the application platform 410 at the server 402 of the database system 400) to analyze conversation data records maintained in a database of the database system (e.g., as data 432 in the database 430). For example, the database may include a table of entries corresponding to data records having the conversation database object type, where the entry for each conversation data record includes a conversation identifier field associated with the respective conversation data record that uniquely identifies the respective conversation, a conversation channel field that identifies the channel used to initialize the conversation (e.g., telephone or a call center, chat bot, text message, a website or web form, a record feed, and/or the like), a representative utterance field that includes a representative utterance or other semantic representation of the respective conversation, and one or more fields that include identifiers or references to the particular cluster groups and/or semantic groups the respective conversation is automatically assigned to, as described herein. The conversation identifier field may be utilized to maintain an association between the particular conversation data record and the transcript, log, feed, thread or other container or collection of utterances associated with the respective conversation. For example, in one implementation, the database includes one or more tables of conversation entries corresponding to each utterance, message or other event of a conversation, where each respective entry for a particular utterance includes a conversation identifier field for maintaining the unique conversation identifier associated with the conversation data record to which the respective utterance belongs, along with other fields identifying the particular user, speaker or actor that is the source of the respective utterance, a particular type or class associated with the source of the respective utterance (e.g., an agent, a bot, an end user, a supervisor, or the like), the textual content of the respective utterance, and the timestamp, duration or other temporal information associated with the respective utterance.", disclosing generating a report including the unique conversation identifier associated with each conversation of the plurality of completed conversations, where a table of entries corresponding to data records reads on a report, and the entry for each conversation data record including a conversation identifier field associated with the respective conversation data record that uniquely identifies the respective conversation reads on the report including the unique conversation identifier associated with each conversation of the plurality of completed conversations.
Therefore, the combination of Akkiraju in view of Alexander discloses the claim 1 limitation "generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time, and (ii) the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time.", where a plurality of scored conversations retrieved from a database for a pre-defined time frame, as disclosed by Akkiraju, includes a conversation identifier field associated with the respective conversations, as taught by Alexander.
Priority
The instant application is a continuation-in-part of U.S. application 17/095,358 and claims benefit under 35 U.S.C. 119(e) to U.S. provisional applications 63/387,638 and 63/479,723. However, claims 1 – 24 of the instant application are not supported by the specification and claims of U.S. application 17/095,358. Therefore, claims 1 – 24 of the instant application have the effective filing date of the earliest provisional application for any claims which are fully supported under the first paragraph of 35 U.S.C. 112 by the provisional application (See MPEP § 2139.01).
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3 – 9, 11 – 13, 15 – 20 and 22 – 24 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claims contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 1, the disclosure does not provide adequate support for the claim limitation "generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time, and (ii) the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time" because the specification does not disclose generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The specification recites, in paragraph 0178, lines 1-4, “In at least one embodiment, each series of interactions with a user 1405 are associated with an identifier, such as a conversation ID. This conversation ID is added to the logs with the action to allow the system 1800 to determine which actions go with each conversation and therefore each user 1405.”, disclosing adding conversation identifiers to conversation logs, but not disclosing generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The specification further recites, in paragraph 0199, lines 1-8, “In some embodiments, the system 1800 may store a plurality of completed conversations. Each conversation of the plurality of completed conversations includes a plurality of interactions between a user 1405 and a voice bot 1565. The system 1800 may also analyze the plurality of completed conversations. The system 1800 may further determine a score for each completed conversation based upon the analysis, the score indicating a quality metric for the corresponding conversation. Additionally, the system 1800 may generate a report based upon the plurality of scores for the plurality of completed conversations.”, disclosing generating a report based upon the plurality of scores for the plurality of completed conversations, but not disclosing generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The introduction of claim changes which involve narrowing the claims by introducing elements or limitations which are not supported by the as-filed disclosure is a violation of the written description requirement of 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph (see MPEP § 2163.05, subsection II).
Claims 3 – 9 and 11 – 12 are also rejected as they depend from claim 1, and thus recite the limitations of claim 1, and therefore contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Regarding claim 13, the disclosure does not provide adequate support for the
claim limitation "generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time, and (ii) the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time" because the specification does not disclose generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The specification recites, in paragraph 0178, lines 1-4, “In at least one embodiment, each series of interactions with a user 1405 are associated with an identifier, such as a conversation ID. This conversation ID is added to the logs with the action to allow the system 1800 to determine which actions go with each conversation and therefore each user 1405.”, disclosing adding conversation identifiers to conversation logs, but not disclosing generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The specification further recites, in paragraph 0199, lines 1-8, “In some embodiments, the system 1800 may store a plurality of completed conversations. Each conversation of the plurality of completed conversations includes a plurality of interactions between a user 1405 and a voice bot 1565. The system 1800 may also analyze the plurality of completed conversations. The system 1800 may further determine a score for each completed conversation based upon the analysis, the score indicating a quality metric for the corresponding conversation. Additionally, the system 1800 may generate a report based upon the plurality of scores for the plurality of completed conversations.”, disclosing generating a report based upon the plurality of scores for the plurality of completed conversations, but not disclosing generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The introduction of claim changes which involve narrowing the claims by introducing elements or limitations which are not supported by the as-filed disclosure is a violation of the written description requirement of 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph (see MPEP § 2163.05, subsection II).
Claims 15 – 20 and 22 – 23 are also rejected as they depend from claim 13, and thus recite the limitations of claim 13, and therefore contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
Regarding claim 24, the disclosure does not provide adequate support for the
claim limitation "generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time, and (ii) the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time" because the specification does not disclose generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The specification recites, in paragraph 0178, lines 1-4, “In at least one embodiment, each series of interactions with a user 1405 are associated with an identifier, such as a conversation ID. This conversation ID is added to the logs with the action to allow the system 1800 to determine which actions go with each conversation and therefore each user 1405.”, disclosing adding conversation identifiers to conversation logs, but not disclosing generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The specification further recites, in paragraph 0199, lines 1-8, “In some embodiments, the system 1800 may store a plurality of completed conversations. Each conversation of the plurality of completed conversations includes a plurality of interactions between a user 1405 and a voice bot 1565. The system 1800 may also analyze the plurality of completed conversations. The system 1800 may further determine a score for each completed conversation based upon the analysis, the score indicating a quality metric for the corresponding conversation. Additionally, the system 1800 may generate a report based upon the plurality of scores for the plurality of completed conversations.”, disclosing generating a report based upon the plurality of scores for the plurality of completed conversations, but not disclosing generating a report that includes the unique conversation identifier associated with each conversation of the plurality of completed conversations completed within the predefined period of time. The introduction of claim changes which involve narrowing the claims by introducing elements or limitations which are not supported by the as-filed disclosure is a violation of the written description requirement of 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph (see MPEP § 2163.05, subsection II).
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.
Claims 1, 3, 5, 13, 15, 17 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Akkiraju et al. (US Patent No. 10,037,768), hereinafter Akkiraju, in view of Alexander et al. (US Patent Application Publication No. 2024/0193373), hereinafter Alexander.
Regarding claim 1, Akkiraju discloses a computer system for analyzing voice bots comprising at least one processor and/or transceiver in communication with at least one memory device (Column 12, lines 6-12, "The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention."), wherein the at least one processor and/or transceiver is programmed to:
store a plurality of completed conversations [in one or more logs] within the at least one memory device, wherein each conversation of the plurality of completed conversations includes a plurality of interactions between a user and a voice bot (Column 7, lines 4-11, "In an embodiment, conversation analysis program 137 receives input (step 202). In other words, conversation analysis program 137 receives input of a conversation occurring in real time. In an embodiment, the conversation is between two people (e.g., a customer and a company representative). In another embodiment, the conversation is between a person (e.g., a customer) and a bot (e.g., an automated response system representing a company)."; Column 8, lines 51-65, "In an embodiment, conversation analysis program 137 determines whether the conversation is done (decision step 210). In other words, conversation analysis program 137 determines whether the on-going conversation between the two parties is completed. In an embodiment (decision step 210, NO branch), conversation analysis program 137 determines that the conversation is not done between the two parties; therefore, conversation analysis program 137 returns to step 202 to receive additional input. In the embodiment (decision step 210, YES branch), conversation analysis program 137 determines that the conversation is done between the two parties; therefore, conversation analysis program 137 proceeds to step 212. In an embodiment, conversation analysis program 137 stores conversation (step 212)."; Column 8, line 64 - Colum 9, line 1, "In an embodiment, conversation analysis program 137 stores conversation (step 212). In other words, conversation analysis program 137 stores the annotated conversation and the results from best practice pattern analyzer 135 to a memory."; A conversation between a person and a bot reads on conversations including interactions between a user and a voice bot, and the conversation analysis program determining that a conversation is done then storing the conversation to a memory reads on storing completed conversations within the at least one memory device.);
extract each conversation of the plurality of conversations completed during a predefined period of time for analysis [based on the corresponding unique conversation identifier] (Column 9, lines 25-29, "In an embodiment, conversation analysis program 137 retrieves the plurality of conversations from a pre-defined time frame (e.g., from the last week, from the last two weeks, from the last month, etc.)."; Retrieving the plurality of conversations from a pre-defined time frame for conversation analysis reads on extracting each conversation of the plurality of conversations completed during a predefined period of time for analysis.);
analyze the plurality of completed conversations (Column 2, lines 10-17, "In an embodiment, various types of annotations such as the tone, emotion, and dialog act for each utterance in a conversation is determined and annotated to a record of the conversation in real time (i.e., as the conversation is on-going). The annotated conversation is analyzed against best practice patterns and suggested dialog acts are provided to the company representative to better satisfy the customer."; Analyzing an annotated conversation against best practice patterns reads on analyzing completed conversations.);
determine a respective score for each completed conversation based upon the analysis, the score indicating a quality metric for the corresponding conversation (Column 5, lines 20-27, "According to an embodiment of the present invention, best practice pattern analyzer 135 is a program, a subprogram of a larger program, an application, a plurality of applications, or mobile application software, which functions to analyze an utterance of a conversation, along with the associated dialog act, emotion, and tone of the utterance, in order to determine the best response option to the utterance by determining a score for each utterance."; The best practice pattern analyzer analyzing an utterance of a conversation and determining a score for each utterance reads on determining a score for each completed conversation based upon the analysis, the score indicating a quality metric for the corresponding conversation.);
and generate a report, the report including [(i) the unique conversation identifier associated with each conversation of] the plurality of completed conversations completed within the predefined period of time, and (ii) the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time (Column 8, line 64 - Column 9, line 8, "In an embodiment, conversation analysis program 137 stores conversation (step 212). In other words, conversation analysis program 137 stores the annotated conversation and the results from best practice pattern analyzer 135 to a memory. In an embodiment, the annotated conversation and the results from best practice pattern analyzer 135 for the analysis of the on-going conversation are stored to a database found in a memory (not shown in FIG. 1) on server device 130. For example, the entire annotated and scored conversation between customer “Jill” and company representative “Dan”, and any recommendations made to “Dan” for proper responses to “Jill” is stored to a memory."; Column 9, lines 21-29, "In an embodiment, conversation analysis program 137 retrieves conversation (step 302). In other words, conversation analysis program 137 retrieves a plurality of annotated and scored conversations from a database stored to a memory (not shown in FIG. 1) on server device 130. In an embodiment, conversation analysis program 137 retrieves the plurality of conversations from a pre-defined time frame (e.g., from the last week, from the last two weeks, from the last month, etc.)."; Storing a plurality of annotated and scored conversations in a database, and retrieving the plurality of scored conversations from a pre-defined time frame, reads on generating a report including the respective score determined for each conversation of the plurality of completed conversations completed within the predefined period of time.).
Akkiraju does not specifically disclose: store a plurality of completed conversations in one or more logs, wherein each conversation is associated with a unique conversation identifier; extract each conversation of the plurality of conversations for analysis based on the corresponding unique conversation identifier; and generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations.
Alexander teaches:
store a plurality of completed conversations in one or more logs, wherein each conversation is associated with a unique conversation identifier (Paragraph 0073, lines 7-13, "For example, the database may include a table of entries corresponding to data records having the conversation database object type, where the entry for each conversation data record includes a conversation identifier field associated with the respective conversation data record that uniquely identifies the respective conversation,"; Paragraph 0075, lines 1-16, "Referring to FIG. 5, in exemplary implementations, the conversation mapping process 500 retrieves or otherwise obtains historical conversational data and analyzes the discrete conversations contained therein to identify a representative utterance with that respective conversation (tasks 502, 504). For example, in exemplary implementations, a computing system, such as the server system 306 or the database system 400, includes or is otherwise associated with a database or other data storage that stores or otherwise maintains transcripts or logs of conversations between different users (e.g., different instances of client device 302) and agents (e.g., different instances of computer system 304), which depending on the scenario could be a human user (e.g., a customer support representative, a sales representative, or other live agent) or an automated actor (e.g., a chat bot)."; Paragraph 0075, lines 20-27, "For example, as described above, in one or more implementations, for each conversation, a corresponding conversation data record is created or otherwise instantiated in the database, with the conversation identifier being utilized to maintain an association between the conversation and the different conversation entry data records that maintain the different utterances associated with the conversation."; A database storing logs of conversations between different users and agents reads on storing completed conversations in one or more logs, and the database entry for each conversation data record including a conversation identifier field associated with the respective conversation data record reads on each conversation being associated with a unique conversation identifier.);
extract each conversation of the plurality of conversations for analysis based on the corresponding unique conversation identifier (Paragraph 0056, lines 1-4, "In one or more implementations, the data storage element 312 stores or otherwise maintains chat messaging data using a storage format and storage location such that the chat messaging data may be later retrieved for use."; Paragraph 0074, lines 1-11, "For a given conversation data record, the conversation identifier associated with that conversation data record may be utilized to retrieve the corresponding conversation entries associated with that conversation, which, in turn, may be analyzed as part of the conversation mapping process 500 to determine the representative utterance or other semantic representation of the respective conversation to be associated with or otherwise assigned to that conversation data record (e.g., by autopopulating the representative utterance field of the conversation data record with the representative utterance)."; The conversation identifier associated with a conversation data record being utilized to retrieve the corresponding conversation entries associated with a conversation to be analyzed reads on extracting each conversation for analysis based on the corresponding unique conversation identifier.);
and generate a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations (Paragraph 0073, lines 1-40, "In one or more implementations, the conversation mapping process 500 is supported or otherwise implemented by an application platform at a server of a database system (e.g., the application platform 410 at the server 402 of the database system 400) to analyze conversation data records maintained in a database of the database system (e.g., as data 432 in the database 430). For example, the database may include a table of entries corresponding to data records having the conversation database object type, where the entry for each conversation data record includes a conversation identifier field associated with the respective conversation data record that uniquely identifies the respective conversation, a conversation channel field that identifies the channel used to initialize the conversation (e.g., telephone or a call center, chat bot, text message, a website or web form, a record feed, and/or the like), a representative utterance field that includes a representative utterance or other semantic representation of the respective conversation, and one or more fields that include identifiers or references to the particular cluster groups and/or semantic groups the respective conversation is automatically assigned to, as described herein. The conversation identifier field may be utilized to maintain an association between the particular conversation data record and the transcript, log, feed, thread or other container or collection of utterances associated with the respective conversation. For example, in one implementation, the database includes one or more tables of conversation entries corresponding to each utterance, message or other event of a conversation, where each respective entry for a particular utterance includes a conversation identifier field for maintaining the unique conversation identifier associated with the conversation data record to which the respective utterance belongs, along with other fields identifying the particular user, speaker or actor that is the source of the respective utterance, a particular type or class associated with the source of the respective utterance (e.g., an agent, a bot, an end user, a supervisor, or the like), the textual content of the respective utterance, and the timestamp, duration or other temporal information associated with the respective utterance."; Including a table of entries corresponding to data records, where the entry for each conversation data record includes a conversation identifier field associated with the respective conversation data record that uniquely identifies the respective conversation, reads on generating a report, the report including (i) the unique conversation identifier associated with each conversation of the plurality of completed conversations.
Alexander is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju to incorporate the teachings of Alexander to implement a database storing logs of conversations between different users and agents, where the database entry for each conversation data record includes a conversation identifier field associated with the respective conversation data record, the conversation identifier associated with a conversation data record is utilized to retrieve the corresponding conversation entries associated with a conversation to be analyzed, and the database includes a table of entries corresponding to data records, where the entry for each conversation data record includes a conversation identifier field associated with the respective conversation data record that uniquely identifies the respective conversation. Doing so would allow for providing structural metadata associated with conversations that allows for performance metrics to be determined across different groups of conversations using the structural metadata (Alexander; Paragraph 0020, lines 1-12).
Regarding claim 3, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1.
Alexander further teaches:
wherein the one or more logs include each interaction between the user and the voice bot (Paragraph 0075, lines 1-16, "Referring to FIG. 5, in exemplary implementations, the conversation mapping process 500 retrieves or otherwise obtains historical conversational data and analyzes the discrete conversations contained therein to identify a representative utterance with that respective conversation (tasks 502, 504). For example, in exemplary implementations, a computing system, such as the server system 306 or the database system 400, includes or is otherwise associated with a database or other data storage that stores or otherwise maintains transcripts or logs of conversations between different users (e.g., different instances of client device 302) and agents (e.g., different instances of computer system 304), which depending on the scenario could be a human user (e.g., a customer support representative, a sales representative, or other live agent) or an automated actor (e.g., a chat bot)."; Logs of conversations between different users and agents, where the agents are chat bots, read on the one or more logs include each interaction between the user and the voice bot.).
Alexander is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander to further incorporate the teachings of Alexander to implement a database storing logs of conversations between different users and agents, where the agents are chat bots. Doing so would allow for providing structural metadata associated with conversations that allows for performance metrics to be determined across different groups of conversations using the structural metadata (Alexander; Paragraph 0020, lines 1-12).
Regarding claim 5, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1.
Akkiraju further discloses:
wherein the at least one processor and/or transceiver is further programmed to identify one or more call sequence events in each conversation of the plurality of completed conversations, wherein the call sequence events for each conversation represents predefined events that occurred during the corresponding conversation (Column 4, lines 6-9, "Machine learning models are trained to predict the dialog act labels of utterances using the extracted linguistic and semantic features."; Column 4, lines 25-31, "Dialog acts include, but are not limited to: counter-greeting, opening statement, question, problem description, reply, acknowledgement, problem resolution, statement, acceptance, rejection, action-directive, apology, excuse, request, ultimatum, seeking permission, complaint, confirm presence, exclamation, ridicule, and command."; Predicting dialog act labels reads on identifying call sequence events, where dialog acts read on predefined events that occurred during the corresponding conversation.).
Regarding claim 13, arguments analogous to claim 1 are applicable.
Regarding claim 15, arguments analogous to claim 3 are applicable.
Regarding claim 17, arguments analogous to claim 5 are applicable.
Regarding claim 24, arguments analogous to claim 1 are applicable. In addition, Akkiraju discloses at least one non-transitory computer-readable media having computer-executable instructions embodied thereon, wherein when executed by a computing device including at least one processor and/or transceiver in communication with at least one memory device and in communication with a user computer device associated with a user (Column 12, lines 6-12, "The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention."), the computer-executable instructions cause the at least one processor and/or transceiver to perform the steps of claim 1.
Claims 4 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Akkiraju in view of Alexander, and further in view of Lubart et al. (US Patent No. 8,391,835), hereinafter Lubart.
Regarding claim 4, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1.
Akkiraju further discloses:
wherein the report includes a list of labels associated with each conversation (Column 4, lines 6-9, "Machine learning models are trained to predict the dialog act labels of utterances using the extracted linguistic and semantic features.").
Akkiraju in view of Alexander does not specifically disclose: wherein the labels include at least one of "no claim number", "call aborted", "lack of information", or "no claim information".
Lubart teaches:
wherein the labels include at least one of "no claim number", "call aborted", "lack of information", or "no claim information" (Column 9, lines 26-32, "A typical call-log can identify the telephone number of the calling or called party, the date and time of the call, a name from ANI data or from a contact list, a type of call (e.g., placed, received, or missed), a duration if the call was successful, and an indication as to whether a call attempt was aborted (e.g., a status) or whether it failed (e.g., an error condition)."; An indication as to whether a call attempt was aborted reads on a "call aborted" label.).
Lubart is considered to be analogous to the claimed invention because it is in the same field of storing conversation. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander to incorporate the teachings of Lubart to record indications in call logs as to whether a call attempt was aborted. Doing so would allow for associating individual phone calls with particular clients and matters to be billed and automatically construct prototype time record entries (Lubart; Column 7, lines 11-30).
Regarding claim 16, arguments analogous to claim 4 are applicable.
Claims 6 – 9, 11 – 12, 18 – 20 and 22 – 23 are rejected under 35 U.S.C. 103 as being unpatentable over Akkiraju in view of Alexander, and further in view of Higgins et al. (US Patent No. 11,496,422), hereinafter Higgins.
Regarding claim 6, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1.
Akkiraju further discloses:
wherein the at least one processor and/or transceiver is further programmed to classify each completed conversation based upon the analysis of the corresponding conversation (Column 10, lines 4-20, "In an embodiment, conversation analysis program 137 ranks conversation (step 306). In other words, conversation analysis program 137 ranks the annotated conversations based on the results of the analysis completed by best practice pattern analyzer 135. According to an embodiment of the present invention, the ranking is done from best to worst based on the number of violations determined by best practice pattern analyzer 135. For example, the fourteen conversations with zero to one violations are ranked “1”, the six conversations with two to three violations are ranked “2”, the five conversations with four to five violations are ranked “3”, the three conversations with six to seven violations are ranked “4”, and the two conversations with eight or more violations are ranked “5”. In other embodiments, ranking is done via sequence alignment algorithms, a sequence-to-one model, and a weighted edit distance, which were previously discussed."; Assigning a ranking to conversations based on the conversation analysis reads on classify each completed conversation based upon the analysis of the corresponding conversation.).
Akkiraju in view of Alexander does not specifically disclose: wherein the analysis of the corresponding conversation includes determining which actions were taken by the voice bot in response to one or more actions of the user.
Higgins teaches:
wherein the analysis of the corresponding conversation includes determining which actions were taken by the voice bot in response to one or more actions of the user (Column 5, line 59 - Column 6, line 6, "In an embodiment, the customer service call center 102 records conversations between customers and the conversation bot agents 104 for evaluation in order to identify any bot states encountered during these conversations. These bot states may include any failure states (e.g., asking for old information, any misunderstandings, inability to assist a customer, inability to transfer the customer to a live agent, certain reprompts, etc.), information gathering states (e.g., customer identification, prompts for new information, requests for confirmation, etc.), transfer states (e.g., offers to transfer to a live agent, prompts to a customer to transfer to a live agent, successful transfers, etc.), assistance states (e.g., provides useful information to a customer, addresses a customer issue, provides accurate responses to queries, etc.), and the like."; Identifying bot states encountered during conversations reads on determining which actions were taken by the voice bot in response to one or more actions of the user.).
Higgins is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander to incorporate the teachings of Higgins to identify bot states encountered during conversations. Doing so would allow for assisting bot managers and builders in identifying particular friction points between bots and customers to allow for real-time identification of bot conversation issues and to train bots to improve conversation flows (Higgins; Column 1, lines 27-31).
Regarding claim 7, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1, but does not specifically disclose: wherein the at least one processor and/or transceiver is further programmed to aggregate the plurality of analyzed conversations to detect one or more errors in the plurality of analyzed conversations, wherein the one or more errors include whether the voice bot correctly interpreted the purpose of an incoming call, correctly directed the incoming call to the proper location, provided the proper response and/or resolved the caller's issue or request.
Higgins teaches:
wherein the at least one processor and/or transceiver is further programmed to aggregate the plurality of analyzed conversations to detect one or more errors in the plurality of analyzed conversations, wherein the one or more errors include whether the voice bot correctly interpreted the purpose of an incoming call, correctly directed the incoming call to the proper location, provided the proper response and/or resolved the caller's issue or request (Column 5, line 59 - Column 6, line 6, "In an embodiment, the customer service call center 102 records conversations between customers and the conversation bot agents 104 for evaluation in order to identify any bot states encountered during these conversations. These bot states may include any failure states (e.g., asking for old information, any misunderstandings, inability to assist a customer, inability to transfer the customer to a live agent, certain reprompts, etc.), information gathering states (e.g., customer identification, prompts for new information, requests for confirmation, etc.), transfer states (e.g., offers to transfer to a live agent, prompts to a customer to transfer to a live agent, successful transfers, etc.), assistance states (e.g., provides useful information to a customer, addresses a customer issue, provides accurate responses to queries, etc.), and the like."; Evaluating recorded conversations between customers and conversation bot agents to identify bot states, where the bot states include failure states, reads on aggregating the plurality of analyzed conversations to detect one or more errors in the plurality of analyzed conversations, a failure state of misunderstandings reads on an error in the voice bot correctly interpreting the purpose of an incoming call, a failure state of inability to transfer the customer to a live agent reads on an error in correctly directing the incoming call to the proper location, a failure state of asking for old information reads on an error in providing the proper response, and a failure state of inability to assist a customer reads on an error in resolving the caller's issue or request.).
Higgins is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander to incorporate the teachings of Higgins to evaluate recorded conversations between customers and conversation bot agents to identify bot states, where the bot states include failure states. Doing so would allow for assisting bot managers and builders in identifying particular friction points between bots and customers to allow for real-time identification of bot conversation issues and to train bots to improve conversation flows (Higgins; Column 1, lines 27-31).
Regarding claim 8, Akkiraju in view of Alexander, and further in view of Higgins, discloses the computer system as claimed in claim 7.
Higgins further teaches:
wherein the at least one processor and/or transceiver is further programmed to report the one or more detected errors (Column 5, lines 59-63, "In an embodiment, the customer service call center 102 records conversations between customers and the conversation bot agents 104 for evaluation in order to identify any bot states encountered during these conversations. These bot states may include any failure states"; Column 10, lines 26-33, "As noted above, the bot state machine learning modeling engine 108 can detect bot states and calculate the MACS for a particular conversation or for each message in the particular conversation in real-time. In an embodiment, the particular conversation can be monitored by a live agent (e.g., human), whereby the live agent may be supplied with the real-time MACS for the conversation and information regarding any detected bot states."; Identifying bot states, where the bot states include failure states, and supplying information regarding any detected bot states to a live agent, reads on reporting the one or more detected errors.).
Higgins is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander and further in view of Higgins to further incorporate the teachings of Higgins to identify bot states, where the bot states include failure states, and supplying information regarding any detected bot states to a live agent. Doing so would allow for assisting bot managers and builders in identifying particular friction points between bots and customers to allow for real-time identification of bot conversation issues and to train bots to improve conversation flows (Higgins; Column 1, lines 27-31).
Regarding claim 9, Akkiraju in view of Alexander, and further in view of Higgins, discloses the computer system as claimed in claim 8.
Higgins further teaches:
wherein the at least one processor and/or transceiver is further programmed to transmit information about the one or more detected errors to a computer device associated with an information technology professional (Column 5, lines 59-63, "In an embodiment, the customer service call center 102 records conversations between customers and the conversation bot agents 104 for evaluation in order to identify any bot states encountered during these conversations. These bot states may include any failure states"; Column 10, lines 4-16, "In an embodiment, the bot state machine learning modeling engine 108 provides the MACS for each conversation to bot builders 116 to allow these bot builders 116 to update the conversation bot agents 104. The MACS for a conversation can be provided via an interface or portal provided by the customer service call center 102 and accessible via a computing device 118 utilized by a bot builder 116. In some instances, the bot state machine learning modeling engine 108 can provide, in addition to MACS for conversations in which conversation bot agents 104 configured by a bot builder 116, the bot states detected and other insights that may be useful to the bot builder 116 for updating the conversation bot agents 104."; Providing the bot states, where the bot states include failure states, to a bot builder through an interface accessible via a computing device utilized by the bot builder reads on transmitting information about the one or more detected errors to a computer device associated with an information technology professional.).
Higgins is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander and further in view of Higgins to further incorporate the teachings of Higgins to provide the bot states, where the bot states include failure states, to a bot builder through an interface accessible via a computing device utilized by the bot builder. Doing so would allow for assisting bot managers and builders in identifying particular friction points between bots and customers to allow for real-time identification of bot conversation issues and to train bots to improve conversation flows (Higgins; Column 1, lines 27-31).
Regarding claim 11, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1, but does not specifically disclose: wherein the at least one processor and/or transceiver is further programmed to analyze each conversation within a first period of time after the conversation has completed.
Higgins teaches:
wherein the at least one processor and/or transceiver is further programmed to analyze each conversation within a first period of time after the conversation has completed (Column 12, lines 36-44, "In some instances, certain features may be applicable once a conversation between a customer and a conversation bot agent has been closed (e.g., calculations performed not in real-time). For instance, the feature extractor 208 may calculate a repeat contact feature, which corresponds to the number of times a customer has re-engaged with a particular brand associated with the customer service call center after the conversation with a conversation bot agent has closed within a predetermined period of time."; Calculating the number of times a customer has re-engaged with a particular brand associated with the customer service call center after the conversation with a conversation bot agent has closed within a predetermined period of time reads on analyze each conversation within a first period of time after the conversation has completed.).
Higgins is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander to incorporate the teachings of Higgins to calculate the number of times a customer has re-engaged with a particular brand associated with the customer service call center after the conversation with a conversation bot agent has closed within a predetermined period of time. Doing so would allow for assisting bot managers and builders in identifying particular friction points between bots and customers to allow for real-time identification of bot conversation issues and to train bots to improve conversation flows (Higgins; Column 1, lines 27-31).
Regarding claim 12, Akkiraju in view of Alexander discloses the computer system as claimed in claim 1, but does not specifically disclose: wherein the at least one processor and/or transceiver is further programmed to: determine a reason for the conversation; and determine if the reason for the conversation was completed during the conversation.
Higgins teaches:
wherein the at least one processor and/or transceiver is further programmed to: determine a reason for the conversation (Column 18, lines 38-42, "The conversation bot agent 714 may automatically identify the customer or other user's intent, as well as key user information (e.g., order number, account number, etc.) that may be used to address the intent."; Identify the user's intent reads on determining a reason for the conversation.);
and determine if the reason for the conversation was completed during the conversation (Column 5, lines 59-63, "In an embodiment, the customer service call center 102 records conversations between customers and the conversation bot agents 104 for evaluation in order to identify any bot states encountered during these conversations. These bot states may include any failure states"; Column 23, lines 46-55, "These bot states may include a failure of the bot to understand a customer's message (e.g., intent, issue, etc.), a bot ignoring the customer, a bot being stuck in a message loop, detection of customer frustration with the bot, an erroneous transfer by the bot to a human agent, a bot performing information gathering in order to resolve an intent, a bot successfully providing assistance to a customer, a bot transferring a conversation to a live agent or other bot more capable of handling the intent, a bot checking understanding of a customer response, and the like."; Identifying bot states, where the bot states include a bot successfully providing assistance to a customer, reads on determining if the reason for the conversation was completed during the conversation.).
Higgins is considered to be analogous to the claimed invention because it is in the same field of conversation analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Akkiraju in view of Alexander to incorporate the teachings of Higgins to identify the user's intent and identify bot states, where the bot states include a bot successfully providing assistance to a customer. Doing so would allow for assisting bot managers and builders in identifying particular friction points between bots and customers to allow for real-time identification of bot conversation issues and to train bots to improve conversation flows (Higgins; Column 1, lines 27-31).
Regarding claim 18, arguments analogous to claim 6 are applicable.
Regarding claim 19, arguments analogous to claim 7 are applicable.
Regarding claim 20, arguments analogous to claim 9 are applicable.
Regarding claim 22, arguments analogous to claim 11 are applicable.
Regarding claim 23, arguments analogous to claim 12 are applicable.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James Boggs whose telephone number is (571)272-2968. The examiner can normally be reached M-F 8:00 AM - 5:00 PM.
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/JAMES BOGGS/Examiner, Art Unit 2657
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