The X-Lance Technical Report for Interspeech 2024 Speech Processing using Discrete Speech Unit Challenge
Discrete speech tokens have been more and more popular in multiple speech processing fields, including automatic speech recognition (ASR), text-to-speech (TTS) and singing voice syn-thesis (SVS). In this paper, we describe the systems developed by the SJTU X-LANCE group for the TTS (acoustic + vocoder), SVS, and ASR tracks in the Interspeech 2024 Speech Processing Using Discrete Speech Unit Challenge. Notably, we achieved 1st rank on the leaderboard<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>https://huggingface.co/spaces/discrete-speech/interspeech2024_discrete_speech_tts_full in the TTS track both with the whole training set and only 1h training data, with the highest UTMOS score and lowest bitrate among all submissions.
Authors
- Chenpeng Du (ORCID: https://orcid.org/0000-0001-5329-0847)
- Kai Yu (ORCID: https://orcid.org/0000-0002-7102-9826)
- H. B. Li
- Hui Zhang (ORCID: https://orcid.org/0009-0009-2257-333X)
- Shuai Wang (ORCID: https://orcid.org/0000-0003-1523-9631)
- Ziyang Ma (ORCID: https://orcid.org/0000-0002-0623-9114)
- Xu Li (ORCID: https://orcid.org/0000-0001-6619-0562)
- Xie Chen (ORCID: https://orcid.org/0009-0004-4458-0753)
- Yifan Yang (ORCID: https://orcid.org/0000-0003-4491-3728)
- Yiwei Guo (ORCID: https://orcid.org/0009-0003-8114-2085)
- Shuai Fan (ORCID: https://orcid.org/0000-0001-7364-7815)
- Hankun Wang (ORCID: https://orcid.org/0000-0003-0338-1809)
- Chenrun Wang
Institutions
- Shanghai Jiao Tong University (CN)
- Shenzhen Research Institute of Big Data (CN)
Publication Details
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1109/iscslp63861.2024.10800009
- Primary Topic
- Speech Recognition and Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00