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20182026
most citedMOSNet: Deep Learning based Objective Assessment for Voice Conversion

262 citations · 1.1k across the 80 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

eess.AS2018

Audiovisual speaker conversion: jointly and simultaneously transforming facial expression and acoustic characteristics

Fuming Fang, Xin Wang, Junichi Yamagishi +1

An audiovisual speaker conversion method is presented for simultaneously transforming the facial expressions and voice of a source speaker into those of a target speaker. Transform…

eess.AS2018★ 1 cited

STFT spectral loss for training a neural speech waveform model

Shinji Takaki, Toru Nakashika, Xin Wang +1

This paper proposes a new loss using short-time Fourier transform (STFT) spectra for the aim of training a high-performance neural speech waveform model that predicts raw continuou…

eess.AS2018★ 3 cited

Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent language

Yusuke Yasuda, Xin Wang, Shinji Takaki +1

End-to-end speech synthesis is a promising approach that directly converts raw text to speech. Although it was shown that Tacotron2 outperforms classical pipeline systems with rega…

eess.AS2018★ 2 cited

Neural source-filter-based waveform model for statistical parametric speech synthesis

Xin Wang, Shinji Takaki, Junichi Yamagishi

Neural waveform models such as the WaveNet are used in many recent text-to-speech systems, but the original WaveNet is quite slow in waveform generation because of its autoregressi…

eess.AS2018★ 2 cited

Investigating accuracy of pitch-accent annotations in neural network-based speech synthesis and denoising effects

Hieu-Thi Luong, Xin Wang, Junichi Yamagishi +1

We investigated the impact of noisy linguistic features on the performance of a Japanese speech synthesis system based on neural network that uses WaveNet vocoder. We compared an i…

eess.AS2018★ 51 cited

Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis

Gustav Eje Henter, Jaime Lorenzo-Trueba, Xin Wang +1

Generating versatile and appropriate synthetic speech requires control over the output expression separate from the spoken text. Important non-textual speech variation is seldom an…