Name
Title | ||
|---|---|---|
Estimation of Number of Chewing Strokes and Swallowing Events by Using LSTM-CTC and Throat Microphone. |
Abstract | ||
|---|---|---|
A personu0027s eating behavior, such as, chewing and swallowing can represents the health conditions of that person. From that viewpoint, we were trying to develop a system that can monitor a personu0027s chewing and swallowing, simply as well as in detail by using sound information recorded near the oropharynx. However, its accuracy was not good enough because of lack of well-labeled training data. In this paper, we propose a technique to gather a large amount of weak-labeled data easily, and leverage it to train the Long Short Term Memory-Connectionist Temporal Classification (LSTM-CTC) model for estimating the number of chewing and swallowing. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/GCCE46687.2019.9015226 | GCCE |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Mehedi Billah | 1 | 0 | 0.34 |
| Taiju Abe | 2 | 0 | 0.34 |
| Akihiro Nakamura | 3 | 0 | 0.34 |
| Hiroshi Mineno | 4 | 130 | 34.93 |
| Masafumi Nishimura | 5 | 112 | 22.77 |
| Takato Saito | 6 | 0 | 0.34 |
| Daizo Ikeda | 7 | 8 | 8.59 |