activity
20152022
most citedDCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement

62 citations · 655 across the 97 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

eess.AS2019★ 3 cited

a novel cross-lingual voice cloning approach with a few text-free samples

Xinyong Zhou, Hao Che, Xiaorui Wang +1

In this paper, we present a cross-lingual voice cloning approach. BN features obtained by SI-ASR model are used as a bridge across speakers and language boundaries. The relationshi…

cs.CL2019★ 14 cited

Espresso: A Fast End-to-end Neural Speech Recognition Toolkit

Yiming Wang, Tongfei Chen, Hainan Xu +7

We present Espresso, an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch and the popular neu…

cs.CL2019★ 6 cited

A New GAN-based End-to-End TTS Training Algorithm

Haohan Guo, Frank K. Soong, Lei He +1

End-to-end, autoregressive model-based TTS has shown significant performance improvements over the conventional one. However, the autoregressive module training is affected by the…

cs.CL2019★ 2 cited

Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS

Haohan Guo, Frank K. Soong, Lei He +1

The end-to-end TTS, which can predict speech directly from a given sequence of graphemes or phonemes, has shown improved performance over the conventional TTS. However, its predict…

eess.AS2019

Improved Speaker-Dependent Separation for CHiME-5 Challenge

Jian Wu, Yong Xu, Shi-Xiong Zhang +4

This paper summarizes several follow-up contributions for improving our submitted NWPU speaker-dependent system for CHiME-5 challenge, which aims to solve the problem of multi-chan…

cs.CL2019★ 4 cited

Building a mixed-lingual neural TTS system with only monolingual data

Liumeng Xue, Wei Song, Guanghui Xu +2

When deploying a Chinese neural text-to-speech (TTS) synthesis system, one of the challenges is to synthesize Chinese utterances with English phrases or words embedded. This paper…

eess.AS2019

Time Domain Audio Visual Speech Separation

Jian Wu, Yong Xu, Shi-Xiong Zhang +4

Audio-visual multi-modal modeling has been demonstrated to be effective in many speech related tasks, such as speech recognition and speech enhancement. This paper introduces a new…