2 citations · 4 across the 4 of their papers we have counts for
5 papers
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…
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…