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NTT Multi-Speaker ASR System for the DASR Task of CHiME-8 Challenge

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arxiv 2409.05554 v1 pith:XCP4PNZE submitted 2024-09-09 eess.AS

Naoyuki Kamo , Naohiro Tawara , Atsushi Ando , Takatomo Kano , Hiroshi Sato , Rintaro Ikeshita , Takafumi Moriya , Shota Horiguchi
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Kohei Matsuura Atsunori Ogawa Alexis Plaquet Takanori Ashihara Tsubasa Ochiai Masato Mimura Marc Delcroix Tomohiro Nakatani Taichi Asami Shoko Araki
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classification eess.AS
keywords systemdasrdiarizationbaselinechime-8developedspeakerachieves
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We present a distant automatic speech recognition (DASR) system developed for the CHiME-8 DASR track. It consists of a diarization first pipeline. For diarization, we use end-to-end diarization with vector clustering (EEND-VC) followed by target speaker voice activity detection (TS-VAD) refinement. To deal with various numbers of speakers, we developed a new multi-channel speaker counting approach. We then apply guided source separation (GSS) with several improvements to the baseline system. Finally, we perform ASR using a combination of systems built from strong pre-trained models. Our proposed system achieves a macro tcpWER of 21.3 % on the dev set, which is a 57 % relative improvement over the baseline.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Exploring Speaker Diarization with Mixture of Experts

    cs.SD 2025-06 conditional novelty 4.0 of 10

    A speaker diarization system that adds a shared-and-soft mixture-of-experts layer to a memory-augmented sequence-to-sequence model reports lower error rates on CHiME-6, DiPCo, and Mixer 6, with some DIHARD-III claims ...

  2. Overlap-Adaptive Hybrid Speaker Diarization and ASR-Aware Observation Addition for MISP 2025 Challenge

    cs.SD 2025-05 conditional novelty 4.0 of 10

    A hybrid diarization and ASR system with a CER-supervised bridging module achieved the best results in two MISP 2025 tracks.

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