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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

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6 papers · 1 filter

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…

cs.SD2021★ 18 cited

Phone-Level Prosody Modelling with GMM-Based MDN for Diverse and Controllable Speech Synthesis

Chenpeng Du, Kai Yu

Generating natural speech with a diverse and smooth prosody pattern is a challenging task. Although random sampling with phone-level prosody distribution has been investigated to g…

cs.SD2021★ 13 cited

Rich Prosody Diversity Modelling with Phone-level Mixture Density Network

Chenpeng Du, Kai Yu

Generating natural speech with diverse and smooth prosody pattern is a challenging task. Although random sampling with phone-level prosody distribution has been investigated to gen…