Name
Abstract | ||
|---|---|---|
The speech interaction in-vehicle was mainly realized by the speech recognition. The human-machine interaction around was usually disturbed by the noise, and the speech received by the receiver was not the original pure speech, so compared to the pure environment, the accuracy of the speech recognition declined so sharply that it could not meet the demand of the practical application of human- machine interaction. So the speech recognition was required to have the strong adaptability and processing capacity to the speech with noise. In this paper, the FastICA algorithm in signal process and statistics was studied and used to separate the driver's speech in the vehicle environment, and realizes the pretreatment in recognizing driver's speech. The effectiveness of the method had been validated in actual vehicle experimental configuration. © 2012 Academy Publisher. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.4304/jmm.7.1.33-40 | Journal of Multimedia |
Keywords | DocType | Volume |
Fast independent component analysis (fast ICA),Human-machine interfaces,Integrated voice-data communication,Intelligent control,Speech processing | Journal | 7 |
Issue | Citations | PageRank |
1 | 2 | 0.41 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jindong Zhang | 1 | 75 | 12.57 |
| Guihe Qin | 2 | 23 | 9.00 |
| Ye Liu | 3 | 9 | 10.07 |