Invention Grant
- Patent Title: Convolution-augmented transformer models
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Application No.: US17139525Application Date: 2020-12-31
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Publication No.: US12079703B2Publication Date: 2024-09-03
- Inventor: Anmol Gulati , Ruoming Pang , Niki Parmar , Jiahui Yu , Wei Han , Chung-Cheng Chiu , Yu Zhang , Yonghui Wu , Shibo Wang , Weikeng Qin , Zhengdong Zhang
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: DORITY & MANNING P.A.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N20/00 ; G10L15/16

Abstract:
Systems and methods can utilize a conformer model to process a data set for various data processing tasks, including, but not limited to, speech recognition, sound separation, protein synthesis determination, video or other image set analysis, and natural language processing. The conformer model can use feed-forward blocks, a self-attention block, and a convolution block to process data to learn global interactions and relative-offset-based local correlations of the input data.
Public/Granted literature
- US20220207321A1 Convolution-Augmented Transformer Models Public/Granted day:2022-06-30
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