Publicação:
Autoregressive decomposition and pole tracking applied to vocal fold nodule signals

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Data

2007-08-01

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Resumo

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. © 2007.

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Autoregressive model, Pole tracking, Vocal nodule, Audio acoustics, Pathology, Perturbation techniques, Signal analysis, Tracking (position), Autoregressive decomposition, Disphonic voice, Signal spectrum, Speech data, Vocal fold nodule signals, Speech recognition

Idioma

Inglês

Como citar

Pattern Recognition Letters, v. 28, n. 11, p. 1360-1367, 2007.

URI

http://hdl.handle.net/11449/69800

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