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In this paper, a HMM based speech recognition system is proposed for the Dysarthric patients. The speech samples recorded from patients with Spastic Dysarthria with mid to high intelligibility are taken from the UA Research database. The speech samples are de-noised using Discrete Wavelet Transform (DWT), after which the MFCC, LPC features are extracted. A comparative study on speech recognition using MFCC and LPC are presented. The recognition efficiency is found to be 68.50% using MFCC features and 66.54% using LPC features.

Isolated Word Recognition for Dysarthric Patients