Invention Application
- Patent Title: SPEECH CODING USING AUTO-REGRESSIVE GENERATIVE NEURAL NETWORKS
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Application No.: US16206823Application Date: 2018-11-30
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Publication No.: US20200176004A1Publication Date: 2020-06-04
- Inventor: Willem Bastiaan Kleijn , Jan K. Skoglund , Alejandro Luebs , Sze Chie Lim
- Applicant: Google LLC
- Main IPC: G10L19/02
- IPC: G10L19/02 ; G10L25/30

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.
Public/Granted literature
- US11024321B2 Speech coding using auto-regressive generative neural networks Public/Granted day:2021-06-01
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