4.5 Article

Classification of stuttering-The ComParE challenge and beyond

Journal

COMPUTER SPEECH AND LANGUAGE
Volume 81, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.csl.2023.101519

Keywords

Dysfluency; Stuttering; ComParE challenge; Paralinguistics; Pathological speech

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The ACM Multimedia 2022 Computational Paralinguistics Challenge (ComParE) focused on the classification of stuttering, aiming to raise awareness and engage a wider research community. Stuttering is a complex speech disorder characterized by blocks, prolongations, and repetitions in speech. Accurate classification of stuttering symptoms is important for the development of self-help tools and specialized automatic speech recognition systems. This paper reviews the challenge contributions, presents improved state-of-the-art classification results, and explores cross-language training using the KSF-C dataset.
The ACM Multimedia 2022 Computational Paralinguistics Challenge (ComParE) featured a sub-challenge on the classification of stuttering in order to bring attention to this important topic and engage a wider research community. Stuttering is a complex speech disorder characterized by blocks, prolongations of sounds and syllables, and repetitions of sounds and words. Accurately classifying the symptoms of stuttering has implications for the development of self-help tools and specialized automatic speech recognition systems (ASR) that can handle atypical speech patterns. This paper provides a review of the challenge contributions and improves upon them with new state-of-the-art classification results for the KSF-C dataset, and explores cross-language training to demonstrate the potential of datasets in multiple languages. To facilitate further research and reproducibility, the full KSF-C dataset, including test-set labels, is also released.

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