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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yelin Kim |
| Copyright Year | 2015 |
| Description | Author affiliation: Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA (Yelin Kim) |
| Abstract | My PhD work aims at developing computational methodologies for automatic emotion recognition from audiovisual behavioral data. A main challenge in automatic emotion recognition is that human behavioral data are highly complex, due to multiple sources that vary and modulate behaviors. My goal is to provide computational frameworks for understanding and controlling for multiple sources of variation in human behavioral data that co-occur with the production of emotion, with the aim of improving automatic emotion recognition systems [1]-[6]. In particular, my research aims at providing representation, modeling, and analysis methods for complex and time-changing behaviors in human audio-visual data by introducing temporal segmentation and time-series analysis techniques. This research contributes to the affective computing community by improving the performance of automatic emotion recognition systems and increasing the understanding of affective cues embedded within complex audio-visual data. |
| Starting Page | 748 |
| Ending Page | 753 |
| File Size | 967627 |
| Page Count | 6 |
| File Format | |
| ISSN | 21568111 |
| e-ISBN | 9781479999538 |
| DOI | 10.1109/ACII.2015.7344653 |
| 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 Multimodal Human perception Emotion estimation Analytical models Affective computing Motion segmentation Temporal Speech recognition Production Speech Variation |
| Content Type | Text |
| Resource Type | Article |
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