Abstract | ||
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The objective is to analyse vocal dysperiodicities in connected speech produced by dysphonic speakers. The analysis involves a variogram-based method that enables tracking instantaneous vocal dysperiodicities. The dysperiodicity trace is summarized by means of the signal-to-dysperiodicity ratio, which has been shown to correlate strongly with the perceived degree of hoarseness of the speaker. Previously, this method has been evaluated on small corpora only. In this article, analyses have been carried out on two corpora comprising over 250 and 700 speakers. This has enabled carrying out multi-frequency band and multi-cue analyses without risking overfitting. The analysis results are compared to the cepstral peak prominence, which is a popular cue that indirectly summarizes vocal dysperiodicities frame-wise. A perceptual rating has been available for the first corpus whereas speakers in the second corpus have been categorized as normal or pathological only. For the first corpus, results show that the correlation with perceptual scores increases statistically significantly for multi-band analysis compared to conventional full-band analysis. Also, combining the cepstral peak prominence with the low-frequency band signal-to-dysperiodicity ratio statistically significantly increases their combined correlation with perceptual scores. The signal-to-dysperiodicity ratios of the two corpora have been separately submitted to principal component analysis. The results show that the first two principal components are interpretable in terms of the degree of dysphonia and the spectral slope, respectively. The clinical relevance of the principal components has been confirmed by linear discriminant analysis. |
Year | DOI | Venue |
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2011 | 10.1016/j.specom.2010.06.010 | Speech Communication |
Keywords | Field | DocType |
principal component analysis,signal-to-dysperiodicity ratio,principal component,connected disordered speech,multi-band analysis,multi-variable analysis,cepstral peak prominence,analysis result,disordered connected speech,multi-cue analysis,conventional full-band analysis,perceptual score,linear discriminant analysis,multi-band dysperiodicity analysis,variogram,low frequency | Connected speech,Variogram,Pattern recognition,Frequency band,Cepstrum,Speech recognition,Correlation,Artificial intelligence,Linear discriminant analysis,Overfitting,Principal component analysis,Mathematics | Journal |
Volume | Issue | ISSN |
53 | 1 | Speech Communication |
Citations | PageRank | References |
8 | 1.15 | 10 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ali Alpan | 1 | 15 | 3.84 |
Y. Maryn | 2 | 14 | 2.81 |
A. Kacha | 3 | 17 | 3.48 |
Francis Grenez | 4 | 82 | 26.07 |
Jean Schoentgen | 5 | 127 | 43.46 |