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 § 103
1. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
2. 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.
3. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Konig et al. (US 20190037077 hereinafter, Konig ‘077) in view of Peleg et al. (US 20230177257 A1 hereinafter, Peleg ‘257).
Regarding claim 1; Konig ‘077 discloses an agent interaction apparatus (Figs. 19A, Computer Devices 1900A),
comprising:
one or more memories (Fig. 19A, Main Memory 1910);
and one or more processors (Fig, 19A, CPU 1905) coupled to the one or more memories (i.e. Fig. 19A shows wherein CPU 1905 is coupled to Main Memory 1910) storing computer-executable instructions (i.e. The central processing unit 1905 is any logic circuitry that responds to and processes instructions fetched from the main memory unit 1910. The main memory unit 1910 may be one or more memory chips capable of storing data and allowing any storage location to be directly accessed by the central processing unit 1905. Paragraph 0135);
configured to cause the agent interaction apparatus to: obtain streaming interaction data contemporaneously generated from an interaction with a user (Fig. 3, Step 305 i.e. In operation 305, the pre-call customer experience automation system (or “application”) 200 (referring to Fig. 2) automatically collects information from a user through a user interface 205. The user input is provided in the form of free speech or text (e.g., unstructured, natural language input). Paragraph 0082);
determine, with a large language model, an intent expressed in the streaming interaction data (Fig. 3, Step 310 i.e. In an embodiment of operation 310 (Fig. 3), the intent inference module 215 (Fig. 2) of the application 200 automatically infers the user's intent from the text of the user input using artificial intelligence or machine learning techniques. Paragraph 0084);
generate a prompt comprising one or more inquiries based on the intent expressed in the streaming interaction data (Fig. 3, Step 315 i.e. In operation 315, the application loads a “script” associated with the given intent, where the script may be stored in a script storage module 220 (Fig. 2). In some embodiments, a script processor module 225 reads the script and provides recommendations to the user through the user interface 205 (e.g., a display device and/or a text-to-speech module associated with the user interface 205). Paragraph 0085);
generate, from the streaming interaction data fed into the large language model and directed by the prompt, text corresponding to one or more responses from the user to the one or more inquiries (i.e. In some embodiments, a script processor module 225 reads the script and provides recommendations to the user through the user interface 205 (e.g., a display device and/or a text-to-speech module associated with the user interface 205). Paragraph 0085);
generate, with the large language model, at least one guidance request based on an absence of a response to, a need for clarification of, or supplemental information to request for at least one of the one or more inquiries based on the one or more responses from the user (i.e. In operation 320 of Fig. 3, the script processor 225 (Fig. 2) prompts the user to supply any missing information (e.g., information that is not available from the user profile 230) to fill in blanks in the template through the user interface 205 prior to initiating a communication with the contact center. In some embodiments, the script processor 225 also requests that the user confirm the accuracy of all of the information that the customer experience automation system 200 will provide to the contact center. Paragraph 0104);
and output the at least one guidance request within a guidance section of an interface communicatively coupled to the agent interaction apparatus (i.e. The application 200 provides functionality to allow a user to supply additional material that will be relevant to the interaction within the application. The functionality may be provided through the UI 205 and may be performed using, for example, the “Share” functionality of mobile operating systems such as Android® and iOS®. Paragraph 0095);
Examiner reasonably believes that Konig ‘077 discloses a prompt as expressed above. However, Examiner cites Peleg ‘257 to cure any deficiencies of Konig ‘077.
Peleg ‘257 discloses prompt (i.e. The user can select the suggested type 625, prompting the writing assistant to display a predetermined template 680 associated with an information request, as shown in Fig. 6d. Paragraph 0122)
Konig ‘077 and Peleg ‘257 are combinable because they are from same field of endeavor of speech systems (Peleg ‘257 at “Background”).
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the speech system as taught by Konig ‘077 by adding the prompt as taught by Peleg ‘257. The motivation for doing so would have been advantageous to better provide a user with a significant level of control in generating language of an intended meaning that agrees with the context of user input text and other available text. Therefore, it would have been obvious to combine Konig ‘077 with Peleg ‘257 to obtain the invention as specified.
Regarding claim 2; Konig ‘077 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to: based on the at least one guidance request, send a request to the user to provide one or more multimedia data uploads related to the intent expressed in the streaming interaction data (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. Paragraph 0095);
obtain the one or more multimedia data uploads based on the request (i.e. The user interface presents options for the user to select any number of collaborative files that have been uploaded into the application by the agent and/or the user for the interaction. Paragraph 0116);
generate, with the large language model, one or more multimedia insights from the one or more multimedia data uploads; and output the one or more multimedia insights within the interface communicatively coupled to the agent interaction apparatus (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. In some embodiments, these documents are provided along with the automatically generated “quick actions” message. The message may serve to prompt the user, by the application 200, to take a photo of the broken part, for inclusion in the material. Paragraph 0095)
Regarding claim 3; Konig ‘077 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to: obtain one or more multimedia data uploads from the user during the interaction (i.e. The user interface presents options for the user to select any number of collaborative files that have been uploaded into the application by the agent and/or the user for the interaction. Paragraph 0116)
generate, with the large language model, one or more multimedia insights from the one or more multimedia data uploads (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. Paragraph 0095);
compare, with the large language model, the one or more multimedia insights and the one or more responses to determine that one or more conflicts are present (i.e. In the example shown in FIG. 6, the application 200 offers specific deals without requiring communication with the provider, such as a call-in to the relevant customer service department. Pricing may also be shown along with data comparisons relevant to the user. For example, promotional offers may be compared to the average usage of the user (e.g., based on the user profile) and current pricing of their plan. Paragraph 0099)
and generate, with the large language model from the one or more conflicts, the at least one guidance request based on the need for clarification of the at least one of the one or more inquires to resolve the one or more conflicts (i.e. Other suggested options that are specific to the user intent in the notification may also be presented, as shown in FIG. 6, such as a “cancel service” option and an option to “search more deals.” Should the user select the “cancel service” option, the application may send a cancellation request to the provider automatically. The application may also search for more deals which fit the user's needs and present these whether the user has selected to cancel their service or just search for additional deals. In some embodiments, these may also be presented to the user as in FIG. 6. Paragraph 0099).
Regarding claim 4; Konig ‘077 discloses wherein to generate, with the large language model, the one or more multimedia insights from the one or more multimedia data uploads, the large language model is directed by the one or more inquiries such that the one or more multimedia insights is based on at least one of the one or more inquiries (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. In some embodiments, these documents are provided along with the automatically generated “quick actions” message. The message may serve to prompt the user, by the application 200, to take a photo of the broken part, for inclusion in the material. Paragraph 0095)
Regarding claim 5; Konig ‘077 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to output, within the interface, an alert contemporaneously with the determination that the one or more conflicts are present (i.e. Other suggested options that are specific to the user intent in the notification may also be presented, as shown in FIG. 6, such as a “cancel service” option and an option to “search more deals.” Should the user select the “cancel service” option, the application may send a cancellation request to the provider automatically. The application may also search for more deals which fit the user's needs and present these whether the user has selected to cancel their service or just search for additional deals. In some embodiments, these may also be presented to the user as in FIG. 6. Paragraph 0099)
Regarding claim 6; Konig ‘077 discloses wherein the interface comprises one or more sections configured to dynamically update content displayed within each of the one or more sections during the interaction with the user based on at least one of the one or more responses from the user to the one or more inquiries or the user guidance response (i.e. The information is provided to the agent before the user is connected through a real-time interaction. Paragraph 0051)
Regarding claim 7; Konig ‘077 discloses wherein the one or more sections comprise a respective section for displaying at least one of: a real-time transcription of the streaming interaction data, the one or more inquiries, the one or more responses, the at least one guidance request, one or more multimedia data uploads, one or more multimedia insights based on the one or more multimedia data uploads, the user guidance response, or combinations thereof (i.e. The user may search for the words “modem cable” in the transcript of the interaction, and the application 200 may display a transcript of the portion of the interaction that contains the query words, along with a view of the screen (e.g., the document being shared) at the corresponding timestamp of the portion of the interaction containing the matching query words in order to retrieve the image 1300 (see, e.g., FIG. 13) Paragraph 0122)
Regarding claim 8; Peleg ‘257 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to: receive a request to provide an interaction summary upon conclusion of the interaction with the user based on at least the one or more responses from the user to the one or more inquiries and the user guidance response (Fig. 36, Steps 3610-3620 i.e. Step 3610 includes acquiring text on which the reading assistant tool is to operate. As described above, the text may be acquired from various types of text files loaded or identified through an interface of the reading assistant tool. Next, at step 3620, the reading assistant tool can analyze and enrich the acquired text. The reading assistant tool can analyze the acquired text to do any of the following actions: identify and/or recognize entities described in the acquired text; summarize facts, information, argument, points, etc. associated with the acquired text; Paragraph 0454-0455);
generate, with the large language model directed by a summary prompt, the interaction summary (Fig. 36, Step 3620 i.e. At step 3620, the reading assistant tool can analyze and enrich the acquired text. The reading assistant tool can analyze the acquired text to do any of the following actions: identify and/or recognize entities described in the acquired text; summarize facts, information, argument, points, etc. associated with the acquired text; Paragraph 0454-0455);
and output the interaction summary within a summary section of the interface communicatively coupled to the agent interaction apparatus (Fig. 36, Step, 3630 i.e. Based on the results of the reading assistant tool's analysis in step 3620, the reading assistant tool can generate various types of outputs at step 3630 to assist a user in working with/understanding the acquired text. Paragraph 0456)
Regarding claim 9; Konig ‘077 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to: receive a user guidance response based on the at least one guidance request (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Paragraph 0095);
and remove the at least one guidance request from the guidance section of the interface when the user guidance response is determined, by the large language model continuously processing the streaming interaction data, to satisfy the at least one guidance request (i.e. Other suggested options that are specific to the user intent in the notification may also be presented, as shown in FIG. 6, such as a “cancel service” option and an option to “search more deals.” Should the user select the “cancel service” option, the application may send a cancellation request to the provider automatically. The application may also search for more deals which fit the user's needs and present these whether the user has selected to cancel their service or just search for additional deals. In some embodiments, these may also be presented to the user as in FIG. 6. Paragraph 0099)
Regarding claim 10; Claim 10 contains substantially the same subject matter as claim 1. Therefore, claim 10 is rejected on the same grounds as claim 1.
Regarding claim 11; Claim 11 contains substantially the same subject matter as claim 2 Therefore, claim 11 is rejected on the same grounds as claim 2.
Regarding claim 12; Claim 12 contains substantially the same subject matter as claim 3. Therefore, claim 12 is rejected on the same grounds as claim 3.
Regarding claim 13; Claim 13 contains substantially the same subject matter as claim 4. Therefore, claim 13 is rejected on the same grounds as claim 4.
Regarding claim 14; Claim 14 contains substantially the same subject matter as claim 5. Therefore, claim 14 is rejected on the same grounds as claim 5.
Regarding claim 15; Claim 15 contains substantially the same subject matter as claim 6. Therefore, claim 15 is rejected on the same grounds as claim 6.
Regarding claim 16; Claim 16 contains substantially the same subject matter as claim 7. Therefore, claim 16 is rejected on the same grounds as claim 7.
Regarding claim 17; Claim 17 contains substantially the same subject matter as claim 8. Therefore, claim 17 is rejected on the same grounds as claim 8.
Regarding claim 18; Konig ‘077 discloses an agent interaction apparatus (Figs. 19A, Computer Devices 1900A),
comprising:
one or more memories (Fig. 19A, Main Memory 1910);
and one or more processors (Fig, 19A, CPU 1905) coupled to the one or more memories (i.e. Fig. 19A shows wherein CPU 1905 is coupled to Main Memory 1910) storing computer-executable instructions (i.e. The central processing unit 1905 is any logic circuitry that responds to and processes instructions fetched from the main memory unit 1910. The main memory unit 1910 may be one or more memory chips capable of storing data and allowing any storage location to be directly accessed by the central processing unit 1905. Paragraph 0135);
configured to cause the agent interaction apparatus to: obtain streaming interaction data contemporaneously generated from an interaction with a user (Fig. 3, Step 305 i.e. In operation 305, the pre-call customer experience automation system (or “application”) 200 (referring to Fig. 2) automatically collects information from a user through a user interface 205. The user input is provided in the form of free speech or text (e.g., unstructured, natural language input). Paragraph 0082);
determine, with a large language model, an intent expressed in the streaming interaction data (Fig. 3, Step 310 i.e. In an embodiment of operation 310 (Fig. 3), the intent inference module 215 (Fig. 2) of the application 200 automatically infers the user's intent from the text of the user input using artificial intelligence or machine learning techniques. Paragraph 0084)
generate a prompt comprising one or more inquiries based on the intent expressed in the streaming interaction data (Fig. 3, Step 315 i.e. In operation 315, the application loads a “script” associated with the given intent, where the script may be stored in a script storage module 220 (Fig. 2). In some embodiments, a script processor module 225 reads the script and provides recommendations to the user through the user interface 205 (e.g., a display device and/or a text-to-speech module associated with the user interface 205). Paragraph 0085);
generate, from the streaming interaction data fed into the large language model and directed by the prompt, text corresponding to one or more responses from the user to the one or more inquiries (i.e. In some embodiments, a script processor module 225 reads the script and provides recommendations to the user through the user interface 205 (e.g., a display device and/or a text-to-speech module associated with the user interface 205). Paragraph 0085);
generate, with the large language model, at least one guidance request based on an absence of a response to, a need for clarification of, or supplemental information to request for at least one of the one or more inquiries based on the one or more responses from the user (i.e. In operation 320 of Fig. 3, the script processor 225 (Fig. 2) prompts the user to supply any missing information (e.g., information that is not available from the user profile 230) to fill in blanks in the template through the user interface 205 prior to initiating a communication with the contact center. In some embodiments, the script processor 225 also requests that the user confirm the accuracy of all of the information that the customer experience automation system 200 will provide to the contact center. Paragraph 0104)
output the at least one guidance request within a guidance section of an interface communicatively coupled to the agent interaction apparatus (i.e. The application 200 provides functionality to allow a user to supply additional material that will be relevant to the interaction within the application. The functionality may be provided through the UI 205 and may be performed using, for example, the “Share” functionality of mobile operating systems such as Android® and iOS®. Paragraph 0095);
based on the at least one guidance request, send a request to the user to provide one or more multimedia data uploads related to the intent expressed in the streaming interaction data (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. Paragraph 0095);
and obtain the one or more multimedia data uploads based on the request (i.e. The user interface presents options for the user to select any number of collaborative files that have been uploaded into the application by the agent and/or the user for the interaction. Paragraph 0116).
Examiner reasonably believes that Konig ‘077 discloses a prompt as expressed above. However, Examiner cites Peleg ‘257 to cure any deficiencies of Konig ‘077.
Peleg ‘257 discloses prompt (i.e. The user can select the suggested type 625, prompting the writing assistant to display a predetermined template 680 associated with an information request, as shown in Fig. 6d. Paragraph 0122)
Konig ‘077 and Peleg ‘257 are combinable because they are from same field of endeavor of speech systems (Peleg ‘257 at “Background”).
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to modify the speech system as taught by Konig ‘077 by adding the prompt as taught by Peleg ‘257. The motivation for doing so would have been advantageous to better provide a user with a significant level of control in generating language of an intended meaning that agrees with the context of user input text and other available text. Therefore, it would have been obvious to combine Konig ‘077 with Peleg ‘257 to obtain the invention as specified.
Regarding claim 19; Konig ‘077 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to: generate, with the large language model, one or more multimedia insights from the one or more multimedia data uploads and output the one or more multimedia insights within the interface communicatively coupled to the agent interaction apparatus (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. In some embodiments, these documents are provided along with the automatically generated “quick actions” message. The message may serve to prompt the user, by the application 200, to take a photo of the broken part, for inclusion in the material. Paragraph 0095)
Regarding claim 20; Konig ‘077 discloses wherein the computer-executable instructions further cause the agent interaction apparatus, when executed by the one or more processors, to: generate, with the large language model, one or more multimedia insights from the one or more multimedia data uploads (i.e. Referring to 505a in FIG. 5, for example, the user may be presented with a selection of descriptions of the files which will be uploaded (‘Last bill’, ‘Previous bill’) and/or a link to directly upload files without a prefilled description of the files. Other examples of descriptions/information include, for example, photographs of broken or failed products, screenshots of error messages, copies of documents, proofs of purchase, etc. Paragraph 0095);
compare, with the large language model, the one or more multimedia insights and the one or more responses to determine that one or more conflicts are present (i.e. In the example shown in FIG. 6, the application 200 offers specific deals without requiring communication with the provider, such as a call-in to the relevant customer service department. Pricing may also be shown along with data comparisons relevant to the user. For example, promotional offers may be compared to the average usage of the user (e.g., based on the user profile) and current pricing of their plan. Paragraph 0099)
and generate, with the large language model from the one or more conflicts, the at least one guidance request based on the need for clarification of the at least one of the one or more inquires to resolve the one or more conflicts (i.e. Other suggested options that are specific to the user intent in the notification may also be presented, as shown in FIG. 6, such as a “cancel service” option and an option to “search more deals.” Should the user select the “cancel service” option, the application may send a cancellation request to the provider automatically. The application may also search for more deals which fit the user's needs and present these whether the user has selected to cancel their service or just search for additional deals. In some embodiments, these may also be presented to the user as in FIG. 6. Paragraph 0099).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARCUS T. RILEY, ESQ. whose telephone number is (571)270-1581. The examiner can normally be reached 9-5 M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hai Phan can be reached at 571-272-6338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MARCUS T. RILEY, ESQ.
Primary Examiner
Art Unit 2654
/MARCUS T RILEY/Primary Examiner, Art Unit 2654
Prosecution Insights