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Humans convey their intentions through the usage of both verbal and nonverbal behaviors during face-to-face communication. Speaker intentions often vary dynamically depending on different nonverbal contexts, such as vocal patterns and facial expressions. As a result, when modeling human language, it is essential to not only consider the literal meaning of the words but also the nonverbal contexts in which these words appear. To better model human language, we first model expressive nonverbal representations by analyzing the fine-grained visual and acoustic patterns that occur during word segments. In addition, we seek to capture the dynamic nature of nonverbal intents by shifting word representations based on the accompanying nonverbal behaviors. To this end, we propose the Recurrent Attended Variation Embedding Network (RAVEN) that models the fine-grained structure of nonverbal subword sequences and dynamically shifts word representations based on nonverbal cues. Our proposed model achieves competitive performance on two publicly available datasets for multimodal sentiment analysis and emotion recognition. We also visualize the shifted word representations in different nonverbal contexts and summarize common patterns regarding multimodal variations of word representations.
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EXTRACTION, SYNTHESIS AND EVALUATION OF CHARISMATIC TEACHERS' NONVERBAL CUES – INITIAL FINDINGS
The paper reports ongoing research aimed at advancing knowledge on the role of expressive, charismatic gestures in education. More specifically, the objectives of the work described in the paper are to(a) measure expressive nonverbal cues from motion captured data and video images of successful instructors at Purdue University, (b) synthesize the identified nonverbal cues using 3D animation technology, and (c) study their effects on students. Current progress towards these goals and initial findings are discussed.
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- Award ID(s):
- 1821894
- PAR ID:
- 10276402
- Date Published:
- Journal Name:
- Proc. of the 270th IIER International Conference, Florence, Italy
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
