30 citations · 44 across the 5 of their papers we have counts for
5 papers
Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkit
Hongji Wang, Chengdong Liang, Shuai Wang +5
Speaker modeling is essential for many related tasks, such as speaker recognition and speaker diarization. The dominant modeling approach is fixed-dimensional vector representation…
Speech BERT Embedding For Improving Prosody in Neural TTS
Liping Chen, Yan Deng, Xi Wang +2
This paper presents a speech BERT model to extract embedded prosody information in speech segments for improving the prosody of synthesized speech in neural text-to-speech (TTS). A…
Exploring Machine Speech Chain for Domain Adaptation and Few-Shot Speaker Adaptation
Fengpeng Yue, Yan Deng, Lei He +1
Machine Speech Chain, which integrates both end-to-end (E2E) automatic speech recognition (ASR) and text-to-speech (TTS) into one circle for joint training, has been proven to be e…
Robust Sequence-to-Sequence Acoustic Modeling with Stepwise Monotonic Attention for Neural TTS
Mutian He, Yan Deng, Lei He
Neural TTS has demonstrated strong capabilities to generate human-like speech with high quality and naturalness, while its generalization to out-of-domain texts is still a challeng…
Modeling Multi-speaker Latent Space to Improve Neural TTS: Quick Enrolling New Speaker and Enhancing Premium Voice
Yan Deng, Lei He, Frank Soong
Neural TTS has shown it can generate high quality synthesized speech. In this paper, we investigate the multi-speaker latent space to improve neural TTS for adapting the system to…