AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection
Abstract
The rapid advancements in speech technologies over the past two decades have led to human-level performance in tasks like automatic speech recognition (ASR) for fluent speech. However, the efficacy of these models diminishes when applied to atypical speech, such as stuttering. This paper introduces AS-70, the first publicly available Mandarin stuttered speech dataset, which stands out as the largest dataset in its category. Encompassing conversational and voice command reading speech, AS-70 includes verbatim manual transcription, rendering it suitable for various speech-related tasks. Furthermore, baseline systems are established, and experimental results are presented for ASR and stuttering event detection (SED) tasks. By incorporating this dataset into the model fine-tuning, significant improvements in the state-of-the-art ASR models, e.g., Whisper and Hubert, are observed, enhancing their inclusivity in addressing stuttered speech.
Cite
@article{arxiv.2406.07256,
title = {AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection},
author = {Rong Gong and Hongfei Xue and Lezhi Wang and Xin Xu and Qisheng Li and Lei Xie and Hui Bu and Shaomei Wu and Jiaming Zhou and Yong Qin and Binbin Zhang and Jun Du and Jia Bin and Ming Li},
journal= {arXiv preprint arXiv:2406.07256},
year = {2024}
}
Comments
Accepted by Interspeech 2024