4 citations · 11 across the 19 of their papers we have counts for
19 papers
Accent-VITS:accent transfer for end-to-end TTS
Linhan Ma, Yongmao Zhang, Xinfa Zhu +4
Accent transfer aims to transfer an accent from a source speaker to synthetic speech in the target speaker's voice. The main challenge is how to effectively disentangle speaker tim…
Vec-Tok Speech: speech vectorization and tokenization for neural speech generation
Xinfa Zhu, Yuanjun Lv, Yi Lei +5
Language models (LMs) have recently flourished in natural language processing and computer vision, generating high-fidelity texts or images in various tasks. In contrast, the curre…
VITS-based Singing Voice Conversion System with DSPGAN post-processing for SVCC2023
Yiquan Zhou, Meng Chen, Yi Lei +2
This paper presents the T02 team's system for the Singing Voice Conversion Challenge 2023 (SVCC2023). Our system entails a VITS-based SVC model, incorporating three modules: a feat…
PromptSpeaker: Speaker Generation Based on Text Descriptions
Yongmao Zhang, Guanghou Liu, Yi Lei +4
Recently, text-guided content generation has received extensive attention. In this work, we explore the possibility of text description-based speaker generation, i.e., using text p…
Zero-Shot Emotion Transfer For Cross-Lingual Speech Synthesis
Yuke Li, Xinfa Zhu, Yi Lei +4
Zero-shot emotion transfer in cross-lingual speech synthesis aims to transfer emotion from an arbitrary speech reference in the source language to the synthetic speech in the targe…
Boosting Multi-Speaker Expressive Speech Synthesis with Semi-supervised Contrastive Learning
Xinfa Zhu, Yuke Li, Yi Lei +3
This paper aims to build a multi-speaker expressive TTS system, synthesizing a target speaker's speech with multiple styles and emotions. To this end, we propose a novel contrastiv…
PromptVC: Flexible Stylistic Voice Conversion in Latent Space Driven by Natural Language Prompts
Jixun Yao, Yuguang Yang, Yi Lei +7
Style voice conversion aims to transform the style of source speech to a desired style according to real-world application demands. However, the current style voice conversion appr…
METTS: Multilingual Emotional Text-to-Speech by Cross-speaker and Cross-lingual Emotion Transfer
Xinfa Zhu, Yi Lei, Tao Li +4
Previous multilingual text-to-speech (TTS) approaches have considered leveraging monolingual speaker data to enable cross-lingual speech synthesis. However, such data-efficient app…
The NPU-MSXF Speech-to-Speech Translation System for IWSLT 2023 Speech-to-Speech Translation Task
Kun Song, Yi lei, Peikun Chen +6
This paper describes the NPU-MSXF system for the IWSLT 2023 speech-to-speech translation (S2ST) task which aims to translate from English speech of multi-source to Chinese speech.…
PromptStyle: Controllable Style Transfer for Text-to-Speech with Natural Language Descriptions
Guanghou Liu, Yongmao Zhang, Yi Lei +4
Style transfer TTS has shown impressive performance in recent years. However, style control is often restricted to systems built on expressive speech recordings with discrete style…
StyleS2ST: Zero-shot Style Transfer for Direct Speech-to-speech Translation
Kun Song, Yi Ren, Yi Lei +5
Direct speech-to-speech translation (S2ST) has gradually become popular as it has many advantages compared with cascade S2ST. However, current research mainly focuses on the accura…
UniSyn: An End-to-End Unified Model for Text-to-Speech and Singing Voice Synthesis
Yi Lei, Shan Yang, Xinsheng Wang +4
Text-to-speech (TTS) and singing voice synthesis (SVS) aim at generating high-quality speaking and singing voice according to textual input and music scores, respectively. Unifying…
Multi-Speaker Expressive Speech Synthesis via Multiple Factors Decoupling
Xinfa Zhu, Yi Lei, Kun Song +3
This paper aims to synthesize the target speaker's speech with desired speaking style and emotion by transferring the style and emotion from reference speech recorded by other spea…
DSPGAN: a GAN-based universal vocoder for high-fidelity TTS by time-frequency domain supervision from DSP
Kun Song, Yongmao Zhang, Yi Lei +5
Recent development of neural vocoders based on the generative adversarial neural network (GAN) has shown obvious advantages of generating raw waveform conditioned on mel-spectrogra…
Glow-WaveGAN 2: High-quality Zero-shot Text-to-speech Synthesis and Any-to-any Voice Conversion
Yi Lei, Shan Yang, Jian Cong +2
The zero-shot scenario for speech generation aims at synthesizing a novel unseen voice with only one utterance of the target speaker. Although the challenges of adapting new voices…
End-to-End Voice Conversion with Information Perturbation
Qicong Xie, Shan Yang, Yi Lei +2
The ideal goal of voice conversion is to convert the source speaker's speech to sound naturally like the target speaker while maintaining the linguistic content and the prosody of…
MsEmoTTS: Multi-scale emotion transfer, prediction, and control for emotional speech synthesis
Yi Lei, Shan Yang, Xinsheng Wang +1
Expressive synthetic speech is essential for many human-computer interaction and audio broadcast scenarios, and thus synthesizing expressive speech has attracted much attention in…
Fine-grained Emotion Strength Transfer, Control and Prediction for Emotional Speech Synthesis
Yi Lei, Shan Yang, Lei Xie
This paper proposes a unified model to conduct emotion transfer, control and prediction for sequence-to-sequence based fine-grained emotional speech synthesis. Conventional emotion…
Learn2Sing: Target Speaker Singing Voice Synthesis by learning from a Singing Teacher
Heyang Xue, Shan Yang, Yi Lei +2
Singing voice synthesis has been paid rising attention with the rapid development of speech synthesis area. In general, a studio-level singing corpus is usually necessary to produc…