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US Patent 11941348 Language model for abstractive summarization

Patent 11941348 was granted and assigned to Twilio on March, 2024 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Twilio
Twilio
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Current Assignee
Twilio
Twilio
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119413480
Patent Inventor Names
Alfredo Láinez Rodrigo0
Luke Percival de Oliveira0
Date of Patent
March 26, 2024
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Patent Application Number
179391760
Date Filed
September 7, 2022
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Patent Citations
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US Patent 9880807 Multi-component viewing tool for contact center agents
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US Patent 9910909 Method and apparatus for extracting journey of life attributes of a user from user interactions
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US Patent 9965726 Adding to a knowledge base using an ontological analysis of unstructured text
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US Patent 10089639 Method and apparatus for building a user profile, for personalization using interaction data, and for generating, identifying, and capturing user data across interactions using unique user identification
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US Patent 10467339 Using machine learning and natural language processing to replace gender biased words within free-form text
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US Patent 10839335 Call center agent performance scoring and sentiment analytics
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US Patent 11165900 Automated real-time call summarization
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US Patent 11170175 Generating replacement sentences for a particular sentiment
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Patent Citations Received
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US Patent 12093298 Apparatus and method for training model for document summarization
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US Patent 12079573 Tool for categorizing and extracting data from audio conversations
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Patent Primary Examiner
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Hassan Mrabi
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CPC Code
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H04M 3/5183
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H04M 2203/2061
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G06F 40/284
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G06F 40/166
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G06F 40/35
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G06F 16/345
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G06N 3/04
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G06N 3/08
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Patent abstract

Methods, systems, and computer programs are presented for abstractive summarization of text by viewing sequence transduction as a language modeling problem. One method comprises an operation for training a machine-learning program to create a machine-learning model that estimates a word to be added to a running summary for the text being summarized. The method further comprises operations for detecting the text to be summarized, initializing the running summary, and performing a plurality of iterations. Each iteration comprises providing, to the machine-learning model, the source text and the running summary, and adding, using the machine-learning model, a new word to the running summary. Further, the method comprises an operation for storing, on a memory, the running summary as the summary of the text.

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