activity
20182024
most citedOverlap-aware diarization: resegmentation using neural end-to-end overlapped speech detection

85 citations · 216 across the 21 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

eess.AS2021★ 2 cited

Multi-Channel End-to-End Neural Diarization with Distributed Microphones

Shota Horiguchi, Yuki Takashima, Paola Garcia +2

Recent progress on end-to-end neural diarization (EEND) has enabled overlap-aware speaker diarization with a single neural network. This paper proposes to enhance EEND by using mul…

eess.AS2021★ 1 cited

Towards Neural Diarization for Unlimited Numbers of Speakers Using Global and Local Attractors

Shota Horiguchi, Shinji Watanabe, Paola Garcia +3

Attractor-based end-to-end diarization is achieving comparable accuracy to the carefully tuned conventional clustering-based methods on challenging datasets. However, the main draw…

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.AS2021★ 61 cited

Encoder-Decoder Based Attractors for End-to-End Neural Diarization

Shota Horiguchi, Yusuke Fujita, Shinji Watanabe +2

This paper investigates an end-to-end neural diarization (EEND) method for an unknown number of speakers. In contrast to the conventional cascaded approach to speaker diarization,…

eess.AS2021★ 27 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.SD2021★ 2 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…