Name
Abstract | ||
|---|---|---|
This letter describes a novel algorithm that is based on autoregressive decomposition and pole tracking used to recognize two patterns of speech data: normal voice and disphonic voice caused by nodules. The presented method relates the poles and the peaks of the signal spectrum which represent the periodic components of the voice. The results show that the perturbation contained in the signal is clearly depicted by pole's positions. Their variability is related to jitter and shimmer. The pole dispersion for pathological voices is about 20% higher than for normal voices, therefore, the proposed approach is a more trustworthy measure than the classical ones. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.patrec.2006.11.016 | Pattern Recognition Letters |
Keywords | Field | DocType |
normal voice,periodic component,autoregressive model,pole tracking,vocal nodule,pole dispersion,autoregressive decomposition,pathological voice,nodule signal,novel algorithm,disphonic voice,signal spectrum,pathology,signal analysis,spectrum,speech recognition | Signal processing,Autoregressive model,Vocal fold nodule,Pattern recognition,Normal voice,Speech recognition,Frequency spectrum,Artificial intelligence,Jitter,Periodic graph (geometry),Mathematics,Gigue | Journal |
Volume | Issue | ISSN |
28 | 11 | Pattern Recognition Letters |
Citations | PageRank | References |
8 | 1.03 | 1 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paulo Rogério Scalassara | 1 | 64 | 6.77 |
| Carlos Dias Maciel | 2 | 109 | 18.95 |
| Rodrigo Capobianco Guido | 3 | 161 | 27.59 |
| José Carlos Pereira | 4 | 95 | 10.90 |
| Everthon Silva Fonseca | 5 | 56 | 5.24 |
| Arlindo Neto Montagnoli | 6 | 16 | 3.45 |
| Sylvio Barbon Júnior | 7 | 50 | 14.05 |
| Lucimar Sasso Vieira | 8 | 20 | 4.85 |
| Fabrício Lopes Sanchez | 9 | 20 | 3.16 |