activity
20192022
most citedNeural Speaker Diarization with Speaker-Wise Chain Rule

41 citations · 110 across the 16 of their papers we have counts for

collaborators

21 papers

cs.CL2022

Better Intermediates Improve CTC Inference

Tatsuya Komatsu, Yusuke Fujita, Jaesong Lee +3

This paper proposes a method for improved CTC inference with searched intermediates and multi-pass conditioning. The paper first formulates self-conditioned CTC as a probabilistic…

cs.CL2022

InterAug: Augmenting Noisy Intermediate Predictions for CTC-based ASR

Yu Nakagome, Tatsuya Komatsu, Yusuke Fujita +2

This paper proposes InterAug: a novel training method for CTC-based ASR using augmented intermediate representations for conditioning. The proposed method exploits the conditioning…

eess.AS2021

Semi-Supervised Training with Pseudo-Labeling for End-to-End Neural Diarization

Yuki Takashima, Yusuke Fujita, Shota Horiguchi +3

In this paper, we present a semi-supervised training technique using pseudo-labeling for end-to-end neural diarization (EEND). The EEND system has shown promising performance compa…

eess.AS2021

End-to-End Speaker Diarization Conditioned on Speech Activity and Overlap Detection

Yuki Takashima, Yusuke Fujita, Shinji Watanabe +3

In this paper, we present a conditional multitask learning method for end-to-end neural speaker diarization (EEND). The EEND system has shown promising performance compared with tr…

eess.AS202127 cited

The Hitachi-JHU DIHARD III System: Competitive End-to-End Neural Diarization and X-Vector Clustering Systems Combined by DOVER-Lap

Shota Horiguchi, Nelson Yalta, Paola Garcia +7

This paper provides a detailed description of the Hitachi-JHU system that was submitted to the Third DIHARD Speech Diarization Challenge. The system outputs the ensemble results of…

cs.SD20212 cited

Online Streaming End-to-End Neural Diarization Handling Overlapping Speech and Flexible Numbers of Speakers

Yawen Xue, Shota Horiguchi, Yusuke Fujita +4

We propose a streaming diarization method based on an end-to-end neural diarization (EEND) model, which handles flexible numbers of speakers and overlapping speech. In our previous…