Abstract
In public speaking, speakers are evaluated on verbal delivery and nonverbal delivery, and in particular, the mouth shape has an important role to support both of these. The mouth shape is mainly set during vowel utterance. We define the mouth shape, which can prompt the pronunciation of the speaker clearly and enrich the facial expression, as a good mouth shape in this research. The authors assume that a good mouth shape can be inferred from the bulging of the platysma muscle in the neck. We aim to support vowel utterances with a good mouth shape, and propose a system to recognize them. Specifically, we measure the uplift of the platysma muscle with photoreflectors and apply a machine learning method to implement a system to judge whether vowel utterances are being performed with a good shape. We conduct an accuracy measurement experiment of the proposed system and report the result. Finally, we describe the application that provides feedback of vowel utterances with a good mouth shape.
Original language | English |
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Title of host publication | Proceedings of the 9th Augmented Human International Conference, AH 2018 |
Publisher | Association for Computing Machinery |
Volume | Part F134484 |
ISBN (Electronic) | 9781450354158 |
DOIs | |
Publication status | Published - 2018 Feb 6 |
Event | 9th Augmented Human International Conference, AH 2018 - Seoul, Korea, Republic of Duration: 2018 Feb 7 → 2018 Feb 9 |
Other
Other | 9th Augmented Human International Conference, AH 2018 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 18/2/7 → 18/2/9 |
Keywords
- Machine Learning.
- Mouth Shape
- Presentation Training
- Public Speech
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software