Automatic analysis of the emotional content of speech in daylong child-centered recordings from a neonatal intensive care unit

Loading...
Thumbnail Image
Journal Title
Journal ISSN
Volume Title
Conference article in proceedings
Date
2021
Major/Subject
Mcode
Degree programme
Language
en
Pages
5
526-530
Series
22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021, Proceedings of the Annual Conference of the International Speech Communication Association
Abstract
Researchers have recently started to study how the emotional speech heard by young infants can affect their developmental outcomes. As a part of this research, hundreds of hours of daylong recordings from preterm infants' audio environments were collected from two hospitals in Finland and Estonia in the context of so-called APPLE study. In order to analyze the emotional content of speech in such a massive dataset, an automatic speech emotion recognition (SER) system is required. However, there are no emotion labels or existing indomain SER systems to be used for this purpose. In this paper, we introduce this initially unannotated large-scale real-world audio dataset and describe the development of a functional SER system for the Finnish subset of the data. We explore the effectiveness of alternative state-of-the-art techniques to deploy a SER system to a new domain, comparing cross-corpus generalization, WGAN-based domain adaptation, and active learning in the task. As a result, we show that the best-performing models are able to achieve a classification performance of 73.4% unweighted average recall (UAR) and 73.2% UAR for a binary classification for valence and arousal, respectively. The results also show that active learning achieves the most consistent performance compared to the two alternatives.
Description
Publisher Copyright: Copyright © 2021 ISCA.
Keywords
Daylong audio, Lena recorder, Real-world audio, Speech analysis, Speech emotion recognition
Other note
Citation
Vaaras , E , Ahlqvist-Bj¨orkroth , S , Drossos , K & R&Die;as¨anen , O 2021 , Automatic analysis of the emotional content of speech in daylong child-centered recordings from a neonatal intensive care unit . in 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 . Proceedings of the Annual Conference of the International Speech Communication Association , International Speech Communication Association (ISCA) , pp. 526-530 , Interspeech , Brno , Czech Republic , 30/08/2021 . https://doi.org/10.21437/Interspeech.2021-303