title: Optimal subband Kalman filter for normal and oesophageal speech enhancement.
abstract: This paper presents the single channel speech enhancement system using subband Kalman filtering by estimating optimal Autoregressive (AR) coefficients and variance for speech and noise, using Weighted Linear Prediction (WLP) and Noise Weighting Function (NWF). The system is applied for normal and Oesophageal speech signals. The method is evaluated by Perceptual Evaluation of Speech Quality (PESQ) score and Signal to Noise Ratio (SNR) improvement for normal speech and Harmonic to Noise Ratio (HNR) for Oesophageal Speech (OES). Compared with previous systems, the normal speech indicates 30% increase in PESQ score, 4 dB SNR improvement and OES shows 3 dB HNR improvement.
authors.affiliation: Deustotech-LIFE, University of Deusto, Bilbao, Spain.
authors.forename: Rizwan
authors.initials: R
authors.lastname: Ishaq
authors.affiliation: Deustotech-LIFE, University of Deusto, Bilbao, Spain.
authors.forename: Begoña
authors.initials: B
authors.lastname: García Zapirain
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography / Q000379:methods*; D013068:Speech Production Measurement / Q000379:methods*; D013072:Speech, Esophageal / Q000379:methods*
keywords: Kalman filter; autoregressive; speech enhancement; weighted linear prediction