NDLI: Recognizing emotions in dialogues with acoustic and lexical features

Content Provider	IEEE Xplore Digital Library
Author	Leimin Tian Moore, J.D. Lai, C.
Copyright Year	2015
Description	Author affiliation: Sch. of Inf., Univ. of Edinburgh, Edinburgh, UK (Leimin Tian; Moore, J.D.; Lai, C.)
Abstract	Automatic emotion recognition has long been a focus of Affective Computing. We aim at improving the performance of state-of-the-art emotion recognition in dialogues using novel knowledge-inspired features and modality fusion strategies. We propose features based on disfluencies and nonverbal vocalisations (DIS-NVs), and show that they are highly predictive for recognizing emotions in spontaneous dialogues. We also propose the hierarchical fusion strategy as an alternative to current feature-level and decision-level fusion. This fusion strategy combines features from different modalities at different layers in a hierarchical structure. It is expected to overcome limitations of feature-level and decision-level fusion by including knowledge on modality differences, while preserving information of each modality.
Starting Page	737
Ending Page	742
File Size	664706
Page Count	6
File Format	PDF
ISSN	21568111
e-ISBN	9781479999538
DOI	10.1109/ACII.2015.7344651
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Emotion recognition Visualization Disfluency Databases Predictive models Feature extraction Dialogue system Acoustics Context modeling
Content Type	Text
Resource Type	Article

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