A Stutter Seldom Comes Alone - Cross-Corpus Stuttering Detection as a Multi-label Problem
Bayerl SP, Wagner D, Baumann I, Hönig F, Bocklet T, Nöth E, Riedhammer K (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: International Speech Communication Association
Book Volume: 2023-August
Pages Range: 1538-1542
Conference Proceedings Title: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Event location: Dublin, IRL
DOI: 10.21437/Interspeech.2023-2026
Abstract
Most stuttering detection and classification research has viewed stuttering as a multi-class classification problem or a binary detection task for each dysfluency type; however, this does not match the nature of stuttering, in which one dysfluency seldom comes alone but rather co-occurs with others. This paper explores multi-language and cross-corpus end-to-end stuttering detection as a multi-label problem using a modified wav2vec 2.0 system with an attention-based classification head and multi-task learning. We evaluate the method using combinations of three datasets containing English and German stuttered speech, one containing speech modified by fluency shaping. The experimental results and an error analysis show that multi-label stuttering detection systems trained on cross-corpus and multi-language data achieve competitive results but performance on samples with multiple labels stays below overall detection results.
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Germany (DE)How to cite
APA:
Bayerl, S.P., Wagner, D., Baumann, I., Hönig, F., Bocklet, T., Nöth, E., & Riedhammer, K. (2023). A Stutter Seldom Comes Alone - Cross-Corpus Stuttering Detection as a Multi-label Problem. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH (pp. 1538-1542). Dublin, IRL: International Speech Communication Association.
MLA:
Bayerl, Sebastian P., et al. "A Stutter Seldom Comes Alone - Cross-Corpus Stuttering Detection as a Multi-label Problem." Proceedings of the 24th International Speech Communication Association, Interspeech 2023, Dublin, IRL International Speech Communication Association, 2023. 1538-1542.
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