TY - JOUR
T1 - In search of the role’s footprints in client-therapist dialogues
AU - Lerner, Anat
AU - Silber-Varod, Vered
AU - Batista, Fernando
AU - Moniz, Helena
N1 - Publisher Copyright:
© 2016, International Speech Communications Association. All rights reserved.
PY - 2016
Y1 - 2016
N2 - The goal of this research is to identify speaker’s role via machine learning of broad acoustic parameters, in order to understand how an occupation, or a role, affects voice characteristics. The examined corpus consists of recordings taken under the same psychological paradigm (Process Work). Four interns were involved in four genuine client-therapist treatment sessions, where each individual had to train her therapeutic skills on her colleague that, in her turn, participated as a client. This uniform setting provided a unique opportunity to examine how role affects speaker’s prosody. By a collection of machine learning algorithms, we tested automatic classification of the role across sessions. Results based on the acoustic properties show high classification rates, suggesting that there are discriminative acoustic features of speaker’s role, as either a therapist or a client.
AB - The goal of this research is to identify speaker’s role via machine learning of broad acoustic parameters, in order to understand how an occupation, or a role, affects voice characteristics. The examined corpus consists of recordings taken under the same psychological paradigm (Process Work). Four interns were involved in four genuine client-therapist treatment sessions, where each individual had to train her therapeutic skills on her colleague that, in her turn, participated as a client. This uniform setting provided a unique opportunity to examine how role affects speaker’s prosody. By a collection of machine learning algorithms, we tested automatic classification of the role across sessions. Results based on the acoustic properties show high classification rates, suggesting that there are discriminative acoustic features of speaker’s role, as either a therapist or a client.
KW - Acoustic features
KW - Client-therapist dialogue
KW - Machine learning
KW - Role identification
KW - Speech analysis
UR - http://www.scopus.com/inward/record.url?scp=84982984292&partnerID=8YFLogxK
U2 - 10.21437/speechprosody.2016-82
DO - 10.21437/speechprosody.2016-82
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AN - SCOPUS:84982984292
SN - 2333-2042
VL - 2016-January
SP - 400
EP - 404
JO - Proceedings of the International Conference on Speech Prosody
JF - Proceedings of the International Conference on Speech Prosody
T2 - 8th Speech Prosody 2016
Y2 - 31 May 2016 through 3 June 2016
ER -