Title :
Pitch tracking and voiced/unvoiced detection in noisy environment using optimal sequence estimation
Author :
Wasserblat, M. ; Gainza, M. ; Dorran, D. ; Domb, Y.
Author_Institution :
Dept. of Electron. Eng., Dublin Inst. of Technol., Dublin
Abstract :
This paper addresses the problem of pitch tracking and voiced/unvoiced detection in noisy speech environments. An algorithm is presented which uses a number of variable thresholds to track pitch contour with minimal error. This is achieved by modeling the pitch tracking problem in such a way that allows the use of optimal estimation methods, such MLSE. The performance of the algorithm is evaluated using the Keele pitch detection database with realistic background noise. Results show best performance in comparison to other state of the art pitch detector and successful pitch tracking is possible in low signal to noise conditions.
Keywords :
signal detection; speech processing; tracking; Keele pitch detection database; harmonic model; noisy speech environment; optimal sequence estimation; pitch contour; pitch tracking; voiced/unvoiced detection; Pitch tracking; harmonic model; voiced/unvoiced detection;
Conference_Titel :
Signals and Systems Conference, 208. (ISSC 2008). IET Irish
Conference_Location :
Galway
Print_ISBN :
978-0-86341-931-7