Invention Grant
- Patent Title: Very deep convolutional neural networks for end-to-end speech recognition
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Application No.: US16692538Application Date: 2019-11-22
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Publication No.: US11080599B2Publication Date: 2021-08-03
- Inventor: Navdeep Jaitly , Yu Zhang , William Chan
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G10L15/16 ; G06N3/04 ; G10L15/02 ; G10L15/22

Abstract:
A speech recognition neural network system includes an encoder neural network and a decoder neural network. The encoder neural network generates an encoded sequence from an input acoustic sequence that represents an utterance. The input acoustic sequence includes a respective acoustic feature representation at each of a plurality of input time steps, the encoded sequence includes a respective encoded representation at each of a plurality of time reduced time steps, and the number of time reduced time steps is less than the number of input time steps. The encoder neural network includes a time reduction subnetwork, a convolutional LSTM subnetwork, and a network in network subnetwork. The decoder neural network receives the encoded sequence and processes the encoded sequence to generate, for each position in an output sequence order, a set of sub string scores that includes a respective sub string score for each substring in a set of substrings.
Public/Granted literature
- US20200090044A1 VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR END-TO-END SPEECH RECOGNITION Public/Granted day:2020-03-19
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