Classification of stuttering – The ComParE challenge and beyond

Sebastian P. Bayerl, Maurice Gerczuk, Anton Batliner, Christian Bergler, Shahin Amiriparian, Björn Schuller, Elmar Nöth, Korbinian Riedhammer

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish
Article number101519
JournalComputer Speech and Language
Volume81
DOIs
StatePublished - Jun 2023
Externally publishedYes

Keywords

  • ComParE challenge
  • Dysfluency
  • Paralinguistics
  • Pathological speech
  • Stuttering

Fingerprint

Dive into the research topics of 'Classification of stuttering – The ComParE challenge and beyond'. Together they form a unique fingerprint.

Cite this