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AudioDec: An Open-source Streaming High-fidelity Neural Audio Codec (2305.16608v1)

Published 26 May 2023 in eess.AS

Abstract: A good audio codec for live applications such as telecommunication is characterized by three key properties: (1) compression, i.e.\ the bitrate that is required to transmit the signal should be as low as possible; (2) latency, i.e.\ encoding and decoding the signal needs to be fast enough to enable communication without or with only minimal noticeable delay; and (3) reconstruction quality of the signal. In this work, we propose an open-source, streamable, and real-time neural audio codec that achieves strong performance along all three axes: it can reconstruct highly natural sounding 48~kHz speech signals while operating at only 12~kbps and running with less than 6~ms (GPU)/10~ms (CPU) latency. An efficient training paradigm is also demonstrated for developing such neural audio codecs for real-world scenarios. Both objective and subjective evaluations using the VCTK corpus are provided. To sum up, AudioDec is a well-developed plug-and-play benchmark for audio codec applications.

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Authors (4)
  1. Yi-Chiao Wu (42 papers)
  2. Israel D. Gebru (10 papers)
  3. Dejan Marković (25 papers)
  4. Alexander Richard (33 papers)
Citations (62)
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