Robust digit recognition with dynamic time warping and recursive least squares

Abstract

Robustness is a key issue in speech recognition. This paper proposes a speech recognition algorithm for Malay digits from 0 to 9. This paper also proposes an algorithm for noise cancellation by using recursive least squares (RLS). This system consists of speech processing inclusive of digit margin and recognition which uses zero crossing and energy calculations. Mel-Frequency Cepstral Coefficient (MFCC) vectors are used to provide an estimate of the vocal tract filter. Meanwhile dynamic time warping (DTW) is used to detect the nearest recorded voice with appropriate global constraint. The global constraint is used to set a valid search region because the variation of the speech rate of the speaker is considered to be limited in a reasonable range, which means that it can prune the unreasonable search space. The algorithm is tested on speech samples that are recorded as a part of a Malay corpus. The results show that the algorithm can recognize almost 80.5% of the Malay digits for all recorded words. By adding RLS noise canceller in the preprocessing stage it increases the accuracy to 92.3%.