Invention Grant
- Patent Title: Multi-task training architecture and strategy for attention-based speech recognition system
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Application No.: US16169512Application Date: 2018-10-24
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Publication No.: US11257481B2Publication Date: 2022-02-22
- Inventor: Jia Cui , Chao Weng , Guangsen Wang , Jun Wang , Chengzhu Yu , Dan Su , Dong Yu
- Applicant: TENCENT AMERICA LLC
- Applicant Address: US CA Palo Alto
- Assignee: TENCENT AMERICA LLC
- Current Assignee: TENCENT AMERICA LLC
- Current Assignee Address: US CA Palo Alto
- Agency: Sughrue Mion, PLLC
- Main IPC: G10L15/06
- IPC: G10L15/06 ; G10L25/03 ; G10L25/54 ; G10L15/10

Abstract:
Methods and apparatuses are provided for performing sequence to sequence (Seq2Seq) speech recognition training performed by at least one processor. The method includes acquiring a training set comprising a plurality of pairs of input data and target data corresponding to the input data, encoding the input data into a sequence of hidden states, performing a connectionist temporal classification (CTC) model training based on the sequence of hidden states, performing an attention model training based on the sequence of hidden states, and decoding the sequence of hidden states to generate target labels by independently performing the CTC model training and the attention model training.
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