Name
Abstract | ||
|---|---|---|
In this paper, we first review several approaches of feature extraction algorithms in robust speech recognition, e.g. Mel frequency cepstral coefficients (MFCC) [1], perceptual linear prediction (PLP) [2] and power-normalized cepstral coefficients (PNCC) [3]. A new feature extraction algorithm for noise robust speech recognition is proposed, in which medium-time processing works as noise suppression module. The details will be described to show that the algorithm is superior. The experimental results prove that our proposed method significantly outperforms state-of-the-art algorithms. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ISCSLP.2012.6423529 | ISCSLP |
Keywords | Field | DocType |
equal-loudness pre-emphasis,perceptual linear predictive,speech recognition,power-normalized cepstral coefficients,feature extraction algorithms,perceptual linear prediction,medium-time noise suppression,pnplp,noise robust speech recognition,pncc,power-normalized plp feature,robust speech recognition,plp,mfcc,mel frequency cepstral coefficients,power normalization,noise suppression module | Mel-frequency cepstrum,Noise suppression,Feature extraction algorithm,Normalization (statistics),Perceptual linear prediction,Pattern recognition,Computer science,Speech recognition,Artificial intelligence | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4673-2505-9 |
Citations | PageRank | References |
1 | 0.35 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lichun Fan | 1 | 3 | 1.07 |
| Dengfeng Ke | 2 | 13 | 4.13 |
| Xiaoyin Fu | 3 | 10 | 2.53 |
| Shixiang Lu | 4 | 19 | 3.39 |
| Bo Xu | 5 | 241 | 36.59 |