788 citations · 1.2k across the 41 of their papers we have counts for
7 papers · 1 filter
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment
Robin Karlsson, Tomoki Hayashi, Keisuke Fujii +3
Recent self-supervised models have demonstrated equal or better performance than supervised methods, opening for AI systems to learn visual representations from practically unlimit…
ESPnet2-TTS: Extending the Edge of TTS Research
Tomoki Hayashi, Ryuichi Yamamoto, Takenori Yoshimura +7
This paper describes ESPnet2-TTS, an end-to-end text-to-speech (E2E-TTS) toolkit. ESPnet2-TTS extends our earlier version, ESPnet-TTS, by adding many new features, including: on-th…
S3PRL-VC: Open-source Voice Conversion Framework with Self-supervised Speech Representations
Wen-Chin Huang, Shu-Wen Yang, Tomoki Hayashi +3
This paper introduces S3PRL-VC, an open-source voice conversion (VC) framework based on the S3PRL toolkit. In the context of recognition-synthesis VC, self-supervised speech repres…
On Prosody Modeling for ASR+TTS based Voice Conversion
Wen-Chin Huang, Tomoki Hayashi, Xinjian Li +2
In voice conversion (VC), an approach showing promising results in the latest voice conversion challenge (VCC) 2020 is to first use an automatic speech recognition (ASR) model to t…
Anomalous Sound Detection Using a Binary Classification Model and Class Centroids
Ibuki Kuroyanagi, Tomoki Hayashi, Kazuya Takeda +1
An anomalous sound detection system to detect unknown anomalous sounds usually needs to be built using only normal sound data. Moreover, it is desirable to improve the system by ef…
Non-autoregressive sequence-to-sequence voice conversion
Tomoki Hayashi, Wen-Chin Huang, Kazuhiro Kobayashi +1
This paper proposes a novel voice conversion (VC) method based on non-autoregressive sequence-to-sequence (NAR-S2S) models. Inspired by the great success of NAR-S2S models such as…