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 |
|---|---|
| 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 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 18/2/7 → 18/2/9 |
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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
Cite this
Recognition and feedback of vowel utterance with a good mouth shape based on sensing Platysma muscle bulging. / Nishimura, Yukihiro; Hashida, Tomoko.
Proceedings of the 9th Augmented Human International Conference, AH 2018. Vol. Part F134484 Association for Computing Machinery, 2018. a18.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Recognition and feedback of vowel utterance with a good mouth shape based on sensing Platysma muscle bulging
AU - Nishimura, Yukihiro
AU - Hashida, Tomoko
PY - 2018/2/6
Y1 - 2018/2/6
N2 - 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.
AB - 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.
KW - Machine Learning.
KW - Mouth Shape
KW - Presentation Training
KW - Public Speech
UR - http://www.scopus.com/inward/record.url?scp=85044266016&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044266016&partnerID=8YFLogxK
U2 - 10.1145/3174910.3174944
DO - 10.1145/3174910.3174944
M3 - Conference contribution
AN - SCOPUS:85044266016
VL - Part F134484
BT - Proceedings of the 9th Augmented Human International Conference, AH 2018
PB - Association for Computing Machinery
ER -