Name
Title | ||
|---|---|---|
Speaker recognition using Mel frequency Cepstral Coefficients (MFCC) and Vector quantization (VQ) techniques |
Abstract | ||
|---|---|---|
This paper presents a fast and accurate automatic voice recognition algorithm. We use Mel frequency Cepstral Coefficient (MFCC) to extract the features from voice and Vector quantization technique to identify the speaker, this technique is usually used in data compression, it allows to model a probability functions by the distribution of different vectors, the results that we achieve were 100% of precision with a database of 10 speakers. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CONIELECOMP.2012.6189918 | Electrical Communications and Computers |
Keywords | Field | DocType |
feature extraction,probability,speaker recognition,vector quantisation,MFCC,Mel frequency cepstral coefficients,automatic voice recognition algorithm,data compression,feature extraction,probability functions,speaker database,speaker identification,speaker recognition,vector quantization techniques,voice quantization technique,Discrete Fourier Transform,MFCC,Speech processing,Vector Quantization,Voice,speaker recognition | Mel-frequency cepstrum,Speech processing,Pattern recognition,Computer science,Vector quantisation,Speech recognition,Feature extraction,Vector quantization,Speaker recognition,Artificial intelligence,Discrete Fourier transform,Data compression | Conference |
ISBN | Citations | PageRank |
978-1-4577-1326-2 | 10 | 0.81 |
References | Authors | |
2 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jorge Martínez | 1 | 95 | 17.02 |
| Héctor Pérez-Meana | 2 | 48 | 15.66 |
| Enrique Escamilla Hernández | 3 | 30 | 4.97 |
| Masahisa Mabo Suzuki | 4 | 10 | 0.81 |
| Perez, H. | 5 | 19 | 3.28 |
| Escamilla, E. | 6 | 10 | 0.81 |