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Chenpeng Du

Shanghai Jiao Tong University

22 papers hereh-index 17898 citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author8
  • middle author14

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • eess.AS9
  • cs.SD6
  • cs.CV4
  • cs.CL3
affiliations
  • Shanghai Jiao Tong University
Homepage
same name
  • Chenpeng Du — 8 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedVQTTS: High-Fidelity Text-to-Speech Synthesis with Self-Supervised VQ Acoustic Feature

43 citations · 178 across the 22 of their papers we have counts for

collaborators
Showing 2023 · cs.SDShow all

4 papers · 2 filters

cs.SD2023

Acoustic BPE for Speech Generation with Discrete Tokens

Feiyu Shen, Yiwei Guo, Chenpeng Du +2

Discrete audio tokens derived from self-supervised learning models have gained widespread usage in speech generation. However, current practice of directly utilizing audio tokens p…

cs.SD2023

DSE-TTS: Dual Speaker Embedding for Cross-Lingual Text-to-Speech

Sen Liu, Yiwei Guo, Chenpeng Du +2

Although high-fidelity speech can be obtained for intralingual speech synthesis, cross-lingual text-to-speech (CTTS) is still far from satisfactory as it is difficult to accurately…

cs.SD2023★ 23 cited

UniCATS: A Unified Context-Aware Text-to-Speech Framework with Contextual VQ-Diffusion and Vocoding

Chenpeng Du, Yiwei Guo, Feiyu Shen +6

The utilization of discrete speech tokens, divided into semantic tokens and acoustic tokens, has been proven superior to traditional acoustic feature mel-spectrograms in terms of n…

cs.SD2023★ 2 cited

Multi-Speaker Multi-Lingual VQTTS System for LIMMITS 2023 Challenge

Chenpeng Du, Yiwei Guo, Feiyu Shen +1

In this paper, we describe the systems developed by the SJTU X-LANCE team for LIMMITS 2023 Challenge, and we mainly focus on the winning system on naturalness for track 1. The aim…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.