Invention Grant
- Patent Title: Detecting affective characteristics of text with gated convolutional encoder-decoder framework
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Application No.: US17822837Application Date: 2022-08-29
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Publication No.: US11886480B2Publication Date: 2024-01-30
- Inventor: Kushal Chawla , Niyati Himanshu Chhaya , Sopan Khosla
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06F16/35
- IPC: G06F16/35 ; G06N3/08 ; G06N3/04 ; G06F40/279 ; G06F40/10 ; G06N20/00

Abstract:
Certain embodiments involve using a gated convolutional encoder-decoder framework for applying affective characteristic labels to input text. For example, a method for identifying an affect label of text with a gated convolutional encoder-decoder model includes receiving, at a supervised classification engine, extracted linguistic features of an input text and a latent representation of an input text. The method also includes predicting, by the supervised classification engine, an affect characterization of the input text using the extracted linguistic features and the latent representation. Predicting the affect characterization includes normalizing and concatenating a linguistic feature representation generated from the extracted linguistic features with the latent representation to generate an appended latent representation. The method also includes identifying, by a gated convolutional encoder-decoder model, an affect label of the input text using the predicted affect characterization.
Public/Granted literature
- US20220414135A1 DETECTING AFFECTIVE CHARACTERISTICS OF TEXT WITH GATED CONVOLUTIONAL ENCODER-DECODER FRAMEWORK Public/Granted day:2022-12-29
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