Title
Dual estimation based vocal tract shape computation
Abstract
This paper presents a new method for direct estimation of vocal tract shape from the speech signal. The method computes cross-sectional areas of uniform-length cylindrical tubes comprising the vocal tract. Cross-sectional areas are calculated from reflection coefficients at tube junctions whose values depend on the areas of adjoining tubes. A new state space representation of the speech production system has been formulated in which reflection coefficients are parameters. The state space model has been constructed using state equations of the glottal flow signal and vocal tract formulated from Liljencrants–Fant model and concatenated tube model respectively. Dual extended Kalman filtering algorithm has been used for estimation of unknown parameters of the system. The estimated reflection coefficients are then used to compute cross-sectional areas of the vocal tract. The performance of proposed technique has been compared to an existing shape estimation method proposed by Wakita. For both synthesized and natural speech signals, the performance of proposed method has been found to be comparable to the existing one. Nevertheless, the Kalman filter algorithm used in proposed method has provisions to tune measurement noise covariance which can be adjusted based on the noise level in speech. Therefore, the performance of proposed method has been seen to be comparatively more robust to noise than the existing technique.
Year
DOI
Venue
2019
10.1007/s10772-018-9538-1
International Journal of Speech Technology
Keywords
Field
DocType
Vocal tract shape, Dual estimation, Dual EKF, Multiple model estimation
Pattern recognition,Computer science,State-space representation,Flow (psychology),Cylinder,Concatenation,Artificial intelligence,Speech production,Vocal tract,Covariance,Computation
Journal
Volume
Issue
ISSN
22
3
1572-8110
Citations 
PageRank 
References 
0
0.34
7
Authors
2
Name
Order
Citations
PageRank
Subhasmita Sahoo151.45
Aurobinda Routray233752.80