Name
Abstract | ||
|---|---|---|
The purpose of this paper is to achieve Japanese syllabary identification without using speech signals. For this purpose, I put an array electrode on the anterior surface of neck and measure BEP signals and I propose a method for classifying Japanese syllabary using BEP signals with SVM. As a first step, we conducted an experiment to identify 10 Japanese syllabary (46 kinds) and rest state. As a result, the average of identification accuracy is 96.6% and least 80%. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/MHS.2015.7438312 | 2015 International Symposium on Micro-NanoMechatronics and Human Science (MHS) |
Keywords | Field | DocType |
Japanese syllabary identification,myoelectric potential,neck muscles,speech signals,array electrode,anterior surface,BEP signal measurement,Japanese syllabary classification | Support vector machine,Speech recognition,Engineering,Syllabary,Neck muscles | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kentaro Suzuki | 1 | 0 | 0.34 |
| Yasuhisa Hasegawa | 2 | 456 | 94.62 |