Anno-MI: A Dataset of Expert-Annotated Counselling Dialogues

Balloccu S.;Kumar V.;Reforgiato Recupero D.
;
Riboni D.
2022-01-01

Abstract

Research on natural language processing for counselling dialogue analysis has seen substantial development in recent years, but access to this area remains extremely limited due to the lack of publicly available expert-annotated therapy conversations. In this work, we introduce AnnoMI, the first publicly and freely accessible dataset of professionally transcribed and expert-annotated therapy dialogues. It consists of 133 conversations that demonstrate high- and low-quality motivational interviewing (MI), an effective counselling technique, and the annotations by domain experts cover key MI attributes. We detail the data collection process including dialogue selection, transcription and annotation. We also present analyses of AnnoMI and discuss its potential applications.
2022
Inglese
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP
978-1-6654-0540-9
2022-May
6177
6181
5
47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Esperti anonimi
23-27 May 2022
Virtual, Online
scientifica
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Wu, Z.; Balloccu, S.; Kumar, V.; Helaoui, R.; Reiter, E.; Reforgiato Recupero, D.; Riboni, D.
273
7
4.1 Contributo in Atti di convegno
reserved
info:eu-repo/semantics/conferencePaper
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