|
|
 |
| |
|
|
|
Robust FHPD Features from Speech Harmonic Analysis for Speaker Identification |
|
|
|
PP: 1591-1598 |
|
|
|
Author(s) |
|
|
|
Shuiping Wang,
Zhenmin Tang,
Ye Jiang,
Ying Chen,
|
|
|
|
Abstract |
|
|
| Speaker identification accuracy decreases significantly in the presence of additive noise. In this paper, we propose a robust
speech feature extraction method, which is based on the harmonic structure of voiced segments. The robust features are composed
of fundamental and harmonic peak data from short-time spectrum. These features are evaluated by thirty speaker data from TIMIT
database and additive noise signals from NOISEX-92 database with clean training and noisy testing samples. Results reflect that
under low SNR (signal-to-noise ratio) environments new features achieve better performance than conventionalMFCC (Mel-Frequency
Cepstral Coefficients) parameters. |
|
|
|
|
|
|
|
