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Supervised Speaker Diarization Using Random Forests: A Tool for Psychotherapy Process Research

Fürer, Lukas and Schenk, Nathalie and Roth, Volker and Steppan, Martin and Schmeck, Klaus and Zimmermann, Ronan. (2020) Supervised Speaker Diarization Using Random Forests: A Tool for Psychotherapy Process Research. Frontiers in Psychology, 11. p. 1726.

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Official URL: https://edoc.unibas.ch/77954/

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Abstract

Speaker diarization is the practice of determining who speaks when in audio recordings. Psychotherapy research often relies on labor intensive manual diarization. Unsupervised methods are available but yield higher error rates. We present a method for supervised speaker diarization based on random forests. It can be considered a compromise between commonly used labor-intensive manual coding and fully automated procedures. The method is validated using the EMRAI synthetic speech corpus and is made publicly available. It yields low diarization error rates (M: 5.61%, STD: 2.19). Supervised speaker diarization is a promising method for psychotherapy research and similar fields.
Faculties and Departments:07 Faculty of Psychology
UniBasel Contributors:Fürer Kugel, Lukas and Schenk, Nathalie and Roth, Volker and Steppan, Martin and Schmeck, Klaus and Zimmermann, Ronan
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Frontiers Media
e-ISSN:1664-1078
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:14 Aug 2020 11:11
Deposited On:14 Aug 2020 11:11

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