66 citations · 71 across the 7 of their papers we have counts for
7 papers
SSL-GMMVC: Interpretable Voice Conversion via Locally Linear GMM Transforms in Self-Supervised Representation Space
Tomoya Tanabu, Hiroshi Nishijima, Daisuke Saito +1
We introduce SSL-GMMVC, an interpretable voice conversion method in self-supervised speech space. The method models paired source-target features with a Gaussian mixture model and…
Leveraging Soft Distributions of SSL-Derived Discrete Speech Tokens for Downstream Inference
Kentaro Onda, Satoru Fukayama, Daisuke Saito +1
Discrete speech tokens obtained from self-supervised learning (SSL) models provide efficient data compression while maintaining strong performance, and have been widely used as int…
A Pilot Study of Applying Sequence-to-Sequence Voice Conversion to Evaluate the Intelligibility of L2 Speech Using a Native Speaker's Shadowings
Haopeng Geng, Daisuke Saito, Nobuaki Minematsu
Utterances by L2 speakers can be unintelligible due to mispronunciation and improper prosody. In computer-aided language learning systems, textual feedback is often provided using…
Simulating Native Speaker Shadowing for Nonnative Speech Assessment with Latent Speech Representations
Haopeng Geng, Daisuke Saito, Nobuaki Minematsu
Evaluating speech intelligibility is a critical task in computer-aided language learning systems. Traditional methods often rely on word error rates (WER) provided by automatic spe…
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder
Yi Zhao, Shinji Takaki, Hieu-Thi Luong +3
Recent neural networks such as WaveNet and sampleRNN that learn directly from speech waveform samples have achieved very high-quality synthetic speech in terms of both naturalness…
The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods
Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda +4
We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016 edition with the aim of providing a common framework for evaluating and comparing different stat…