Classification of stuttering – The ComParE challenge and beyond

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, prolongat...

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Bibliographic Details
Published in:Computer speech & language 2023-06, Vol.81, p.101519, Article 101519
Main Authors: Bayerl, Sebastian P., Gerczuk, Maurice, Batliner, Anton, Bergler, Christian, Amiriparian, Shahin, Schuller, Björn, Nöth, Elmar, Riedhammer, Korbinian
Format: Article
Language:English
Subjects:
ComParE challenge
Dysfluency
Paralinguistics
Pathological speech
Stuttering
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Summary: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. •Review of contributions to the ACM ComParE 2022 stuttering sub-challenge.•Release of the full KSF-C dataset release, including test-set labels.•State-of-the-art stuttering classification results based on wav2vec 2.0.•Cross-language stuttering classification training.
ISSN:0885-2308
1095-8363
DOI:10.1016/j.csl.2023.101519