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LMCodec: A Low Bitrate Speech Codec With Causal Transformer Models (2303.12984v1)

Published 23 Mar 2023 in cs.SD and eess.AS

Abstract: We introduce LMCodec, a causal neural speech codec that provides high quality audio at very low bitrates. The backbone of the system is a causal convolutional codec that encodes audio into a hierarchy of coarse-to-fine tokens using residual vector quantization. LMCodec trains a Transformer LLM to predict the fine tokens from the coarse ones in a generative fashion, allowing for the transmission of fewer codes. A second Transformer predicts the uncertainty of the next codes given the past transmitted codes, and is used to perform conditional entropy coding. A MUSHRA subjective test was conducted and shows that the quality is comparable to reference codecs at higher bitrates. Example audio is available at https://mjenrungrot.github.io/chrome-media-audio-papers/publications/lmcodec.

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Authors (7)
  1. Teerapat Jenrungrot (5 papers)
  2. Michael Chinen (12 papers)
  3. W. Bastiaan Kleijn (39 papers)
  4. Jan Skoglund (23 papers)
  5. Zalán Borsos (18 papers)
  6. Neil Zeghidour (39 papers)
  7. Marco Tagliasacchi (37 papers)
Citations (18)
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