2 citations · 6 across the 11 of their papers we have counts for
12 papers
StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion
Zhichao Wang, Yuanzhe Chen, Xinsheng Wang +2
StreamVoice has recently pushed the boundaries of zero-shot voice conversion (VC) in the streaming domain. It uses a streamable language model (LM) with a context-aware approach to…
StreamVoice: Streamable Context-Aware Language Modeling for Real-time Zero-Shot Voice Conversion
Zhichao Wang, Yuanzhe Chen, Xinsheng Wang +2
Recent language model (LM) advancements have showcased impressive zero-shot voice conversion (VC) performance. However, existing LM-based VC models usually apply offline conversion…
LM-VC: Zero-shot Voice Conversion via Speech Generation based on Language Models
Zhichao Wang, Yuanzhe Chen, Lei Xie +2
Language model (LM) based audio generation frameworks, e.g., AudioLM, have recently achieved new state-of-the-art performance in zero-shot audio generation. In this paper, we explo…
Multi-level Temporal-channel Speaker Retrieval for Zero-shot Voice Conversion
Zhichao Wang, Liumeng Xue, Qiuqiang Kong +4
Zero-shot voice conversion (VC) converts source speech into the voice of any desired speaker using only one utterance of the speaker without requiring additional model updates. Typ…
Zero-Shot Accent Conversion using Pseudo Siamese Disentanglement Network
Dongya Jia, Qiao Tian, Kainan Peng +5
The goal of accent conversion (AC) is to convert the accent of speech into the target accent while preserving the content and speaker identity. AC enables a variety of applications…
Delivering Speaking Style in Low-resource Voice Conversion with Multi-factor Constraints
Zhichao Wang, Xinsheng Wang, Lei Xie +3
Conveying the linguistic content and maintaining the source speech's speaking style, such as intonation and emotion, is essential in voice conversion (VC). However, in a low-resour…
Streaming Voice Conversion Via Intermediate Bottleneck Features And Non-streaming Teacher Guidance
Yuanzhe Chen, Ming Tu, Tang Li +7
Streaming voice conversion (VC) is the task of converting the voice of one person to another in real-time. Previous streaming VC methods use phonetic posteriorgrams (PPGs) extracte…
Multi-channel end-to-end neural network for speech enhancement, source localization, and voice activity detection
Yuan Chen, Yicheng Hsu, Mingsian R. Bai
Speech enhancement and source localization has been active research for several decades with a wide range of real-world applications. Recently, the Deep Complex Convolution Recurre…
Cloning one's voice using very limited data in the wild
Dongyang Dai, Yuanzhe Chen, Li Chen +6
With the increasing popularity of speech synthesis products, the industry has put forward more requirements for personalized speech synthesis: (1) How to use low-resource, easily a…
Semi-supervised Learning for Multi-speaker Text-to-speech Synthesis Using Discrete Speech Representation
Tao Tu, Yuan-Jui Chen, Alexander H. Liu +1
Recently, end-to-end multi-speaker text-to-speech (TTS) systems gain success in the situation where a lot of high-quality speech plus their corresponding transcriptions are availab…
Meta Learning for End-to-End Low-Resource Speech Recognition
Jui-Yang Hsu, Yuan-Jui Chen, Hung-yi Lee
In this paper, we proposed to apply meta learning approach for low-resource automatic speech recognition (ASR). We formulated ASR for different languages as different tasks, and me…
End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning
Tao Tu, Yuan-Jui Chen, Cheng-chieh Yeh +1
End-to-end text-to-speech (TTS) has shown great success on large quantities of paired text plus speech data. However, laborious data collection remains difficult for at least 95% o…