96 citations · 272 across the 20 of their papers we have counts for
6 papers · 1 filter
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge
Mutian He, Jingzhou Yang, Lei He +1
End-to-end TTS requires a large amount of speech/text paired data to cover all necessary knowledge, particularly how to pronounce different words in diverse contexts, so that a neu…
Cross-speaker Style Transfer with Prosody Bottleneck in Neural Speech Synthesis
Shifeng Pan, Lei He
Cross-speaker style transfer is crucial to the applications of multi-style and expressive speech synthesis at scale. It does not require the target speakers to be experts in expres…
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…
On Addressing Practical Challenges for RNN-Transducer
Rui Zhao, Jian Xue, Jinyu Li +3
In this paper, several works are proposed to address practical challenges for deploying RNN Transducer (RNN-T) based speech recognition system. These challenges are adapting a well…
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…
Multilingual Byte2Speech Models for Scalable Low-resource Speech Synthesis
Mutian He, Jingzhou Yang, Lei He +1
To scale neural speech synthesis to various real-world languages, we present a multilingual end-to-end framework that maps byte inputs to spectrograms, thus allowing arbitrary inpu…