95 citations · 240 across the 11 of their papers we have counts for
11 papers
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech
Xin Zhang, Iván Vallés-Pérez, Andreas Stolcke +5
Stuttering is a speech disorder where the natural flow of speech is interrupted by blocks, repetitions or prolongations of syllables, words and phrases. The majority of existing au…
Peking Opera Synthesis via Duration Informed Attention Network
Yusong Wu, Shengchen Li, Chengzhu Yu +4
Peking Opera has been the most dominant form of Chinese performing art since around 200 years ago. A Peking Opera singer usually exhibits a very strong personal style via introduci…
DurIAN-SC: Duration Informed Attention Network based Singing Voice Conversion System
Liqiang Zhang, Chengzhu Yu, Heng Lu +6
Singing voice conversion is converting the timbre in the source singing to the target speaker's voice while keeping singing content the same. However, singing data for target speak…
Synthesising Expressiveness in Peking Opera via Duration Informed Attention Network
Yusong Wu, Shengchen Li, Chengzhu Yu +4
This paper presents a method that generates expressive singing voice of Peking opera. The synthesis of expressive opera singing usually requires pitch contours to be extracted as t…
Learning Singing From Speech
Liqiang Zhang, Chengzhu Yu, Heng Lu +5
We propose an algorithm that is capable of synthesizing high quality target speaker's singing voice given only their normal speech samples. The proposed algorithm first integrate s…
PitchNet: Unsupervised Singing Voice Conversion with Pitch Adversarial Network
Chengqi Deng, Chengzhu Yu, Heng Lu +2
Singing voice conversion is to convert a singer's voice to another one's voice without changing singing content. Recent work shows that unsupervised singing voice conversion can be…
Minimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition
Chao Weng, Chengzhu Yu, Jia Cui +2
In this work, we propose minimum Bayes risk (MBR) training of RNN-Transducer (RNN-T) for end-to-end speech recognition. Specifically, initialized with a RNN-T trained model, MBR tr…
DurIAN: Duration Informed Attention Network For Multimodal Synthesis
Chengzhu Yu, Heng Lu, Na Hu +9
In this paper, we present a generic and robust multimodal synthesis system that produces highly natural speech and facial expression simultaneously. The key component of this syste…
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
Chih-Kuan Yeh, Jianshu Chen, Chengzhu Yu +1
We consider the problem of training speech recognition systems without using any labeled data, under the assumption that the learner can only access to the input utterances and a p…
UTD-CRSS Systems for 2016 NIST Speaker Recognition Evaluation
Chunlei Zhang, Fahimeh Bahmaninezhad, Shivesh Ranjan +3
This document briefly describes the systems submitted by the Center for Robust Speech Systems (CRSS) from The University of Texas at Dallas (UTD) to the 2016 National Institute of…
Advances in All-Neural Speech Recognition
G. Zweig, C. Yu, J. Droppo +1
This paper advances the design of CTC-based all-neural (or end-to-end) speech recognizers. We propose a novel symbol inventory, and a novel iterated-CTC method in which a second sy…