Name
Abstract | ||
|---|---|---|
In this paper we propose a new approach based on energy-adaptive matching pursuits to improve sinusoidal modelling of speech and audio signals for coding and recognition purposes. To reduce the complexity of the algorithm, an over-complete dictionary composed of complex exponentials is used and an efficient implementation is presented. An analysis-synthesis windows scheme that avoids overlapping is proposed, too. Experimental results show evidence of the advantages of the proposed method for sinusoidal modelling of speech and audio signals compared to some others proposed in the literature. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-44871-6_121 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
matching pursuit | Audio signal,Speech processing,Speech coding,Exponential function,Adaptive method,Computer science,Speech recognition,Coding (social sciences),Codec2,Energy method | Conference |
Volume | ISSN | Citations |
2652 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro Vera-Candeas | 1 | 94 | 12.51 |
| Nicolás Ruiz-Reyes | 2 | 59 | 9.86 |
| Martinez-Munoz, D. | 3 | 26 | 4.31 |
| Curpian-Alonso, J. | 4 | 0 | 1.35 |
| Manuel Rosa-Zurera | 5 | 192 | 36.27 |
| M. J. Lucena-lopez | 6 | 1 | 0.70 |