- 专利标题: Asynchronous optimization for sequence training of neural networks
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申请号: US17644362申请日: 2021-12-15
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公开(公告)号: US11557277B2公开(公告)日: 2023-01-17
- 发明人: Georg Heigold , Erik McDermott , Vincent O. VanHoucke , Andrew W. Senior , Michiel A. U. Bacchiani
- 申请人: Google LLC
- 申请人地址: US CA Mountain View
- 专利权人: Google LLC
- 当前专利权人: Google LLC
- 当前专利权人地址: US CA Mountain View
- 代理机构: Honigman LLP
- 代理商 Brett A. Krueger; Grant Griffith
- 主分类号: G10L15/06
- IPC分类号: G10L15/06 ; G10L15/16 ; G10L15/183 ; G06N3/04
摘要:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.
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