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ICASSP
2011
IEEE

Glottal inverse filtering using stabilised weighted linear prediction

12 years 7 months ago
Glottal inverse filtering using stabilised weighted linear prediction
This paper presents and evaluates an inverse filtering technique of the speech signal which is based on the Stabilized Weighted Linear Prediction (SWLP) of speech [1]. SWLP emphasizes the speech samples that fit the underlying speech production model well, by imposing temporal weighting of the square of the residual signal. The performance of SWLP is compared to the conventional Linear Prediction based inverse filtering techniques, such as the Autocorrelation and Closed Phase Covariance method. All the inverse filtering approaches are evaluated on a database of speech signals generated by a physical model of the voice production system. Results show that the estimated glottal flows using SWLP are closer to the original glottal flow than those estimated by the Autocorrelation approach, while its performance is comparable to the Closed Phase Covariance approach.
George P. Kafentzis, Yannis Stylianou, Paavo Alku
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors George P. Kafentzis, Yannis Stylianou, Paavo Alku
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