Noise robust acoustic signal processing using a Hybrid approach for speech recognition

The paper proposes English digit recognition using a Hybrid approach for both speaker dependent and independent mode in clean and noisy situations. This work uses Discrete Hidden Markov Model for digit recognition where DHMM is modeled with quantized vectors. Mel Frequency Cepstral coefficients is used at feature extraction stage to extract feature vectors of all digits and it also uses filters that operates on cepstrum obtained from MFCC to smoothens signal. This work uses Empirical Mode Decomposition (EMD) process for the noises separation from speech signals. The database containing digits from Zero to Nine is used for the work. This works propose that recognition rate of English digits in noisy environment can be improved by applying filters to the cepstrum obtained from MFCC and by using EMD along with Genetic Algorithm for noise removal