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eess.AS2025

Can We Really Repurpose Multi-Speaker ASR Corpus for Speaker Diarization?

Shota Horiguchi, Naohiro Tawara, Takanori Ashihara +2

Neural speaker diarization is widely used for overlap-aware speaker diarization, but it requires large multi-speaker datasets for training. To meet this data requirement, large dat…

eess.AS2025

Mitigating Non-Target Speaker Bias in Guided Speaker Embedding

Shota Horiguchi, Takanori Ashihara, Marc Delcroix +2

Obtaining high-quality speaker embeddings in multi-speaker conditions is crucial for many applications. A recently proposed guided speaker embedding framework, which utilizes speec…

eess.AS2025

Pretraining Multi-Speaker Identification for Neural Speaker Diarization

Shota Horiguchi, Atsushi Ando, Marc Delcroix +1

End-to-end speaker diarization enables accurate overlap-aware diarization by jointly estimating multiple speakers' speech activities in parallel. This approach is data-hungry, requ…

eess.AS2025

Microphone Array Geometry Independent Multi-Talker Distant ASR: NTT System for the DASR Task of the CHiME-8 Challenge

Naoyuki Kamo, Naohiro Tawara, Atsushi Ando +15

In this paper, we introduce a multi-talker distant automatic speech recognition (DASR) system we designed for the DASR task 1 of the CHiME-8 challenge. Our system performs speaker…

eess.AS2024

Guided Speaker Embedding

Shota Horiguchi, Takafumi Moriya, Atsushi Ando +4

This paper proposes a guided speaker embedding extraction system, which extracts speaker embeddings of the target speaker using speech activities of target and interference speaker…

eess.AS2024

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

Naoyuki Kamo, Naohiro Tawara, Atsushi Ando +15

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-en…