Abstract
There exists a major incompatibility in emotion labeling framework among emotional speech corpora, that is, category-based and dimension-based. Commonizing these requires inter-corpus emotion labeling according to both frameworks, but doing this by human annotators is too costly for most cases. This paper examines the possibility of automatic cross-corpus emotion labeling. In order to evaluate the effectiveness of the automatic labeling, a comprehensive emotion annotation for two conversational corpora, UUDB and OGVC, was performed. With a state-of-the-art machine learning technique, dimensional and categorical emotion estimation models were trained and tested against the two corpora. For the emotion dimension estimation, the automatic cross-corpus emotion labeling for the different corpus was effective for the dimensions of aroused-sleepy, dominant-submissive and interested-indifferent, showing only slight performance degradation against the result for the same corpus. On the other hand, the performance for the emotion category estimation was not sufficient.- Anthology ID:
- L16-1634
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 4019–4023
- Language:
- URL:
- https://aclanthology.org/L16-1634
- DOI:
- Cite (ACL):
- Hiroki Mori, Atsushi Nagaoka, and Yoshiko Arimoto. 2016. Accuracy of Automatic Cross-Corpus Emotion Labeling for Conversational Speech Corpus Commonization. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4019–4023, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Accuracy of Automatic Cross-Corpus Emotion Labeling for Conversational Speech Corpus Commonization (Mori et al., LREC 2016)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/L16-1634.pdf