AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection

• DOI: 10.21437/interspeech.2024-918
• Publication Date: 2024-09-01T07:10:12Z
• Authors: Rong Gong; Hongfei Xue; Lezhi Wang; Xin Xu; Qisheng Li; Lei Xie; Hui Bu; Shaomei Wu; Jiaming Zhou; Yong Qin; Binbin Zhang; Jun Du; Jia Bin; Ming Li
• Keywords: FOS: Computer and information sciences; Sound (cs.SD); Artificial Intelligence (cs.AI); Computer Science - Artificial Intelligence; Audio and Speech Processing (eess.AS); FOS: Electrical engineering, electronic engineering, information engineering; Computer Science - Sound; Electrical Engineering and Systems Science - Audio and Speech Processing

Accepted by Interspeech 2024<br/>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.<br/>