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Supervised Speaker Diarization Using Random Forests: A Tool for Psychotherapy Process Research
Ist Teil von
Frontiers in psychology, 2020-07, Vol.11, p.1726-1726
Ort / Verlag
Frontiers Research Foundation
Erscheinungsjahr
2020
Link zum Volltext
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
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.