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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 2019Show all

13 papers · 1 filter

cs.SD2019

Transformation of low-quality device-recorded speech to high-quality speech using improved SEGAN model

Seyyed Saeed Sarfjoo, Xin Wang, Gustav Eje Henter +3

Nowadays vast amounts of speech data are recorded from low-quality recorder devices such as smartphones, tablets, laptops, and medium-quality microphones. The objective of this res…

eess.AS2019★ 1 cited

Transferring neural speech waveform synthesizers to musical instrument sounds generation

Yi Zhao, Xin Wang, Lauri Juvela +1

Recent neural waveform synthesizers such as WaveNet, WaveGlow, and the neural-source-filter (NSF) model have shown good performance in speech synthesis despite their different meth…

eess.AS2019★ 11 cited

ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech

Xin Wang, Junichi Yamagishi, Massimiliano Todisco +37

Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is v…

eess.AS2019

Modeling of Rakugo Speech and Its Limitations: Toward Speech Synthesis That Entertains Audiences

Shuhei Kato, Yusuke Yasuda, Xin Wang +3

We have been investigating rakugo speech synthesis as a challenging example of speech synthesis that entertains audiences. Rakugo is a traditional Japanese form of verbal entertain…

eess.AS2019

Effect of choice of probability distribution, randomness, and search methods for alignment modeling in sequence-to-sequence text-to-speech synthesis using hard alignment

Yusuke Yasuda, Xin Wang, Junichi Yamagishi

Sequence-to-sequence text-to-speech (TTS) is dominated by soft-attention-based methods. Recently, hard-attention-based methods have been proposed to prevent fatal alignment errors,…

eess.AS2019★ 5 cited

Initial investigation of an encoder-decoder end-to-end TTS framework using marginalization of monotonic hard latent alignments

Yusuke Yasuda, Xin Wang, Junichi Yamagishi

End-to-end text-to-speech (TTS) synthesis is a method that directly converts input text to output acoustic features using a single network. A recent advance of end-to-end TTS is du…