Invention Grant
- Patent Title: Topical vector-quantized variational autoencoders for extractive summarization of video transcripts
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Application No.: US17361878Application Date: 2021-06-29
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Publication No.: US12147771B2Publication Date: 2024-11-19
- Inventor: Sangwoo Cho , Franck Dernoncourt , Timothy Jeewun Ganter , Trung Huu Bui , Nedim Lipka , Varun Manjunatha , Walter Chang , Hailin Jin , Jonathan Brandt
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: F. CHAU & ASSOCIATES, LLC
- Main IPC: G06F40/35
- IPC: G06F40/35 ; G06F40/279

Abstract:
System and methods for a text summarization system are described. In one example, a text summarization system receives an input utterance and determines whether the utterance should be included in a summary of the text. The text summarization system includes an embedding network, a convolution network, an encoding component, and a summary component. The embedding network generates a semantic embedding of an utterance. The convolution network generates a plurality of feature vectors based on the semantic embedding. The encoding component identifies a plurality of latent codes respectively corresponding to the plurality of feature vectors. The summary component identifies a prominent code among the latent codes and to select the utterance as a summary utterance based on the prominent code.
Public/Granted literature
- US20220414338A1 TOPICAL VECTOR-QUANTIZED VARIATIONAL AUTOENCODERS FOR EXTRACTIVE SUMMARIZATION OF VIDEO TRANSCRIPTS Public/Granted day:2022-12-29
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