Name
Abstract | ||
|---|---|---|
The paper describes a novel method for discrete speech recognition based on spoken Arabic digit recognition by means of wavelet neural network in which Morlet wavelet is introduced to the hidden layer. The speech signal is extracted by means of Mel Frequency Cepstral Coefficients (MFCCs) and followed by vector quantization (VQ). The experimental results obtained on a spoken Arabic digit dataset proved that it could achieve better accuracy and need less learning time than the proposed method. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICSMC.2011.6083880 | SMC |
Keywords | Field | DocType |
discrete speech recognition,arabic digits recognition,speech signal extraction,spoken arabic digit dataset,speech recognition,morlet wavelet,vq,hidden layer,vector quantization,wavelet transforms,vector quantisation,cepstral analysis,feature extraction,wavelet neural networks,natural language processing,mfcc,spoken arabic digit recognition,neural nets,mel frequency cepstral coefficients,mel frequency cepstral coefficient,vectors,accuracy,speech | Mel-frequency cepstrum,Wavelet neural network,Pattern recognition,Computer science,Speech recognition,Feature extraction,Vector quantization,Arabic numerals,Artificial intelligence,Artificial neural network,Morlet wavelet,Wavelet transform | Conference |
Volume | Issue | ISSN |
null | null | 1062-922X |
ISBN | Citations | PageRank |
978-1-4577-0652-3 | 4 | 0.46 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaohui Hu | 1 | 4 | 1.14 |
| Lv-Jun Zhan | 2 | 4 | 1.14 |
| Yun Xue | 3 | 6 | 5.30 |
| Wei-Xing Zhou | 4 | 206 | 15.05 |
| Liangjun Zhang | 5 | 213 | 20.23 |