| Autor: |
Pang Yi Liu, Guan Long Hong, Jian-Da Wu |
| Rok vydání: |
2014 |
| Předmět: |
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| Zdroj: |
Applied Mechanics and Materials. :1287-1292 |
| ISSN: |
1662-7482 |
| Popis: |
This study presents a driver identification system using voice analysis for a vehicle security system. The structure of the proposed system has three parts. The first procedure is speech pre-processing, the second is feature extraction of sound signals, and the third is classification of driver voice. Initially, a database of sound signals for several drivers was established. The volume and zero-crossing rate (ZCR) of sound are used to detect the voice end-point in order to reduce data computation. Then the Auto-correlation Function (ACF) and Average Magnitude Difference Function (AMDF) methods are applied to retrieve the voice pitch features. Finally these features are used to identify the drivers by a General Regression Neural Network (GRNN). The experimental results show that the development of this voice identification system can use fewer feature vectors of pitch to obtain a good recognition rate. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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