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20242026
most citedThe CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization

1 citations · 1 across the 10 of their papers we have counts for

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eess.AS2026

LALM-as-a-Judge: Benchmarking Large Audio-Language Models for Safety Evaluation in Multi-Turn Spoken Dialogues

Amir Ivry, Shinji Watanabe

Evaluation of socially unsafe content in spoken dialogues remains text-centric, missing prosody and transcription failures. We present LALM-as-a-Judge, which includes an open bench…

eess.AS2025

Recent Trends in Distant Conversational Speech Recognition: A Review of CHiME-7 and 8 DASR Challenges

Samuele Cornell, Christoph Boeddeker, Taejin Park +9

The CHiME-7 and 8 distant speech recognition (DASR) challenges focus on multi-channel, generalizable, joint automatic speech recognition (ASR) and diarization of conversational spe…

eess.AS2024

Deep Speech Synthesis from Multimodal Articulatory Representations

Peter Wu, Bohan Yu, Kevin Scheck +6

The amount of articulatory data available for training deep learning models is much less compared to acoustic speech data. In order to improve articulatory-to-acoustic synthesis pe…

eess.AS2024

End-to-End Speech Recognition with Pre-trained Masked Language Model

Yosuke Higuchi, Tetsuji Ogawa, Tetsunori Kobayashi +1

We present a novel approach to end-to-end automatic speech recognition (ASR) that utilizes pre-trained masked language models (LMs) to facilitate the extraction of linguistic infor…

eess.AS2024★ 1 cited

The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization

Samuele Cornell, Taejin Park, Steve Huang +6

This paper presents the CHiME-8 DASR challenge which carries on from the previous edition CHiME-7 DASR (C7DASR) and the past CHiME-6 challenge. It focuses on joint multi-channel di…

eess.AS2024

EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation

Julius Richter, Yi-Chiao Wu, Steven Krenn +5

We release the EARS (Expressive Anechoic Recordings of Speech) dataset, a high-quality speech dataset comprising 107 speakers from diverse backgrounds, totaling in 100 hours of cle…