185 citations · 501 across the 25 of their papers we have counts for
10 papers · 1 filter
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
Xu Tan, Jiawei Chen, Haohe Liu +11
Text to speech (TTS) has made rapid progress in both academia and industry in recent years. Some questions naturally arise that whether a TTS system can achieve human-level quality…
A Survey on Neural Speech Synthesis
Xu Tan, Tao Qin, Frank Soong +1
Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural speech given text, is a hot research topic in speech, language, and machine learning co…
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…
s-Transformer: Segment-Transformer for Robust Neural Speech Synthesis
Xi Wang, Huaiping Ming, Lei He +1
Neural end-to-end text-to-speech (TTS) , which adopts either a recurrent model, e.g. Tacotron, or an attention one, e.g. Transformer, to characterize a speech utterance, has achiev…
Improving pronunciation assessment via ordinal regression with anchored reference samples
Bin Su, Shaoguang Mao, Frank Soong +3
Sentence level pronunciation assessment is important for Computer Assisted Language Learning (CALL). Traditional speech pronunciation assessment, based on the Goodness of Pronuncia…
Transfer Learning for Improving Singing-voice Detection in Polyphonic Instrumental Music
Yuanbo Hou, Frank K. Soong, Jian Luan +1
Detecting singing-voice in polyphonic instrumental music is critical to music information retrieval. To train a robust vocal detector, a large dataset marked with vocal or non-voca…
Improving LPCNet-based Text-to-Speech with Linear Prediction-structured Mixture Density Network
Min-Jae Hwang, Eunwoo Song, Ryuichi Yamamoto +2
In this paper, we propose an improved LPCNet vocoder using a linear prediction (LP)-structured mixture density network (MDN). The recently proposed LPCNet vocoder has successfully…
Forward-Backward Decoding for Regularizing End-to-End TTS
Yibin Zheng, Xi Wang, Lei He +4
Neural end-to-end TTS can generate very high-quality synthesized speech, and even close to human recording within similar domain text. However, it performs unsatisfactory when scal…
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…
LP-WaveNet: Linear Prediction-based WaveNet Speech Synthesis
Min-Jae Hwang, Frank Soong, Eunwoo Song +3
We propose a linear prediction (LP)-based waveform generation method via WaveNet vocoding framework. A WaveNet-based neural vocoder has significantly improved the quality of parame…