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Multilingual Stutter Event Detection for English, German, and Mandarin Speech

arXiv 2603.26939 ↗First posted 27 Mar 2026cs.SD cs.CL eess.AScited by 0

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Abstract (arXiv)

This paper presents a multi-label stuttering detection system trained on multi-corpus, multilingual data in English, German, and Mandarin.By leveraging annotated stuttering data from three languages and four corpora, the model captures language-independent characteristics of stuttering, enabling robust detection across linguistic contexts. Experimental results demonstrate that multilingual training achieves performance comparable to and, in some cases, even exceeds that of previous systems. These findings suggest that stuttering exhibits cross-linguistic consistency, which supports the development of language-agnostic detection systems. Our work demonstrates the feasibility and advantages of using multilingual data to improve generalizability and reliability in automated stuttering detection.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 29 references that are in the map. First posted on arXiv 27 Mar 2026.

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17 of 29 references.

References · 17

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,609
  4. 2022Self-supervised Learning with Random-projection Quantizer for Speech Recognitioncited by 158
  5. 2020Multi-task self-supervised learning for Robust Speech Recognitioncited by 127
  6. 2021SEP-28k: A Dataset for Stuttering Event Detection From Podcasts With People Who Stuttercited by 51
  7. 2019Detecting Multiple Speech Disfluencies using a Deep Residual Network with Bidirectional Long Short-Term Memorycited by 27
  8. 2022Detecting Dysfluencies in Stuttering Therapy Using wav2vec 2.0cited by 26
  9. 2022KSoF: The Kassel State of Fluency Dataset -- A Therapy Centered Dataset of Stutteringcited by 21
  10. 2021StutterNet: Stuttering Detection Using Time Delay Neural Networkcited by 20
  11. 2024YOLO-Stutter: End-to-end Region-Wise Speech Dysfluency Detectioncited by 16
  12. 2022The Influence of Dataset Partitioning on Dysfluency Detection Systemscited by 9
5 more
  1. 2023A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problemcited by 9
  2. 2022Robust Stuttering Detection via Multi-task and Adversarial Learningcited by 6
  3. 2024AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detectioncited by 5
  4. 2025Boli: A dataset for understanding stuttering experience and analyzing stuttered speechcited by 3
  5. 2024Findings of the 2024 Mandarin Stuttering Event Detection and Automatic Speech Recognition Challengecited by 2

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