Name
Title | ||
|---|---|---|
A Comparative Study of Feature Extraction Algorithms on ANN Based Speaker Model for Speaker Recognition Applications |
Abstract | ||
|---|---|---|
In this paper we present a comparative study of usefulness of four of the most popular feature extraction algorithm in Artificial Neural Network based Text dependent speaker recognition system. The network uses multi-layered perceptron with backpropagation learning. We show the performance of the network for two phrases with a population of 25 speakers. The result shows normalized Mel Frequency Cepstral Coefficients performing better in false acceptance rate as well as in size of the network for an admissible error rate. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30499-9_185 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
artificial neural network,multi layer perceptron,backpropagation,error rate,speaker recognition,feature extraction,mel frequency cepstral coefficient | Mel-frequency cepstrum,Population,Computer science,Speaker recognition,Artificial intelligence,Artificial neural network,Pattern recognition,Word error rate,Feature extraction,Speech recognition,Backpropagation,Perceptron,Machine learning | Conference |
Volume | ISSN | Citations |
3316 | 0302-9743 | 3 |
PageRank | References | Authors |
0.43 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Goutam Saha | 1 | 255 | 23.17 |
| Pankaj Kumar | 2 | 361 | 43.64 |
| Sandipan Chakroborty | 3 | 31 | 3.34 |