# US 10,319,370 B2 · System and method for data-driven socially customized models for language generation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,319,370 B2 - Document ID: US10319370B2 - Status: Granted - Kind: B2 - Application number: 15/978,529 - Filed: 2018-05-14 - Published: 2018-09-13 - Granted: 2019-06-11 - Earliest claimed: 2014-05-13 - Assignees: AT&T Intellectual Property I, L.P. - Applicants: AT&T Intellectual Property I, L.P. - Inventors: Taniya Mishra; Alistair D. Conkie; Svetlana Stoyanchev - Web page: https://patentgrep.com/patent/US10319370B2 ## CPC - G10L 15/07: to the speaker - G10L 13/027: Concept to speech synthesisers; Generation of natural phrases from machine-based concepts (generation of parameters for speech synthesis out of text G10L13/08) - G10L 15/02: Feature extraction for speech recognition; Selection of recognition unit - G10L 15/1815: {Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning} - G10L 15/183: using context dependencies, e.g. language models - G10L 17/00: Speaker identification or verification techniques - G10L 17/22: Interactive procedures; Man-machine interfaces - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING ## Abstract Systems, methods, and computer-readable storage devices for generating speech using a presentation style specific to a user, and in particular the user's social group. Systems configured according to this disclosure can then use the resulting, personalized, text and/or speech in a spoken dialogue or presentation system to communicate with the user. For example, a system practicing the disclosed method can receive speech from a user, identify the user, and respond to the received speech by applying a personalized natural language generation model. The personalized natural language generation model provides communications which can be specific to the identified user. ## Claims ### Claim 1 A method comprising: receiving a literary narrative; generating, via a processor, a personalized natural language generation model based on a stylistic analysis of the literary narrative, wherein the stylistic analysis identifies connections between two or more of a personality independent quotation lattice, a personality independent attribute, a personality dependent attribute, and a speaker within the literary narrative; and applying the personalized natural language generation model to a spoken dialog system. ### Claim 2 (depends on 1) The method of claim 1, further comprising: identifying, via a processor configured to perform speech analysis, an identity of a user based on characteristics of received speech during a dialog between the user and the spoken dialog system, to yield a user identification. ### Claim 3 (depends on 2) The method of claim 2, wherein the generating of the personalized natural language generation model is further based on the user identification. ### Claim 4 (depends on 1) The method of claim 1, further comprising: applying the personalized natural language generation model to the spoken dialog system while performing, as part of a dialog, one of automatic speech recognition or natural language generation. ### Claim 5 (depends on 1) The method of claim 1, wherein stylistic analysis further comprises: identifying speakers in the literary narrative, to yield identified speakers; attributing quoted utterances in the literary narrative to the identified speakers, to yield a quotation lattice; identifying the personality independent attributes and the personality dependent attributes of the quoted utterances within the quotation lattice; and organizing the quotation lattice based on the personality independent attributes, to yield the personality independent quotation lattice. ### Claim 6 (depends on 1) The method of claim 1, wherein the stylistic analysis further comprises identifying a lexical difference between quotations associated with distinct demographics of speakers within the literary narrative. ### Claim 7 (depends on 1) The method of claim 1, wherein the stylistic analysis further comprises identifying a semantic difference between quotations associated with distinct demographics of speakers within the literary narrative. ### Claim 8 (depends on 1) The method of claim 1, wherein the stylistic analysis comprises identifying both a lexical difference and a semantic difference between quotations associated with distinct demographics of speakers within the literary narrative. ### Claim 9 (depends on 2) The method of claim 2, wherein the identifying of the user from the received speech further comprises performing a prosody analysis of the received speech. ### Claim 10 A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a literary narrative; generating a personalized natural language generation model based on a stylistic analysis of the literary narrative, wherein the stylistic analysis identifies connections between two or more of a personality independent quotation lattice, a personality independent attribute, a personality dependent attribute, and a speaker within the literary narrative; and applying the personalized natural language generation model to a spoken dialog system. ### Claim 11 (depends on 10) The system of claim 10, the computer-readable storage medium further stores instructions stored which, when executed by the processor, cause the processor to perform operations further comprising: identifying an identity of a user based on characteristics of received speech during a dialog between the user and the spoken dialog system, to yield a user identification. ### Claim 12 (depends on 11) The system of claim 11, wherein the generating of the personalized natural language generation model is further based on the user identification. ### Claim 13 (depends on 1) The system of claim 1, the computer-readable storage medium further stores instructions stored which, when executed by the processor, cause the processor to perform operations further comprising: applying the personalized natural language generation model to the spoken dialog system while performing, as part of a dialog, one of automatic speech recognition or natural language generation. ### Claim 14 (depends on 1) The system of claim 1, wherein stylistic analysis further comprises: identifying speakers in the literary narrative, to yield identified speakers; attributing quoted utterances in the literary narrative to the identified speakers, to yield a quotation lattice; identifying the personality independent attributes and the personality dependent attributes of the quoted utterances within the quotation lattice; and organizing the quotation lattice based on the personality independent attributes, to yield the personality independent quotation lattice. ### Claim 15 (depends on 10) The system of claim 10, wherein the stylistic analysis further comprises identifying a lexical difference between quotations associated with distinct demographics of speakers within the literary narrative. ### Claim 16 (depends on 10) The system of claim 10, wherein the stylistic analysis further comprises identifying a semantic difference between quotations associated with distinct demographics of speakers within the literary narrative. ### Claim 17 (depends on 10) The system of claim 10, wherein the stylistic analysis comprises identifying both a lexical difference and a semantic difference between quotations associated with distinct demographics of speakers within the literary narrative. ### Claim 18 (depends on 11) The system of claim 11, wherein the identifying of the user from the received speech further comprises performing a prosody analysis of the received speech. ### Claim 19 A non-transitory computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a literary narrative; generating a personalized natural language generation model based on a stylistic analysis of the literary narrative, wherein the stylistic analysis identifies connections between two or more of a personality independent quotation lattice, a personality independent attribute, a personality dependent attribute, and a speaker within the literary narrative; and applying the personalized natural language generation model to a spoken dialog system. ### Claim 20 (depends on 19) The non-transitory computer-readable storage device of claim 19, wherein the non-transitory computer-readable storage device stores further instructions stored which, when executed by the computing device, cause the computing device to perform operations further comprising: identifying an identity of a user based on characteristics of received speech during a dialog between the user and the spoken dialog system, to yield a user identification.