A Reinforcement Learning Approach to Speech Coding
نویسندگان
چکیده
Speech coding is an essential technology for digital cellular communications, voice over IP, and video conferencing systems. For more than 25 years, the main approach to speech these applications has been block-based analysis-by-synthesis linear predictive coding. An alternative that less successful sample-by-sample tree of speech. We reformulate this latter as a multistage reinforcement learning problem with L step lookahead incorporates exploration exploitation adapt model parameters control analysis/synthesis process on basis. The minimization spectrally shaped reconstruction error finite depth manages complexity serves effective stand in overall subjective evaluation reconstructed quality intelligibility. Different policies attempt persistently excite system states encourage are studied evaluated. resulting methods produce competitive most popular codec utilized today. This new formulation provides insights opens up directions design performance improvement.
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ژورنال
عنوان ژورنال: Information
سال: 2022
ISSN: ['2078-2489']
DOI: https://doi.org/10.3390/info13070331