Name
Abstract | ||
|---|---|---|
This paper presents a biometric personal-authentication method that exploits acoustic characteristics of human ears. It transmits a probe signal into the ear and receives its reflection, which contains personal identity information about the shape of the ear canal. Based on a study of effective and efficient acoustic feature representation and the use of audio equipment suitable for acquiring features with low within-individual variability, the proposed method achieves a promising equal error rate of 0.97% with only 12 feature components. A prototype system for Android smartphones is also presented. |
Year | Venue | Field |
|---|---|---|
2016 | Asia-Pacific Signal and Information Processing Association Annual Summit and Conference | Headphones,Mel-frequency cepstrum,Authentication,Android (operating system),Computer science,Word error rate,Speech recognition,Acoustics,Biometrics,Audio equipment,Ear canal |
DocType | ISSN | Citations |
Conference | 2309-9402 | 2 |
PageRank | References | Authors |
0.38 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takayuki Arakawa | 1 | 7 | 2.32 |
| Takafumi Koshinaka | 2 | 32 | 7.62 |
| Shohei Yano | 3 | 2 | 0.38 |
| Hideki Irisawa | 4 | 2 | 0.38 |
| Ryoji Miyahara | 5 | 5 | 0.78 |
| Hitoshi Imaoka | 6 | 4 | 4.86 |