Robustness is a key issue in speech recognition. A speech recognition algorithm for Malay digits from zero to nine and an algorithm for noise cancellation by using recursive least squares (RLS) is proposed in this article. This system consisted of speech processing inclusive of digit margin and recognition using zero crossing and energy calculations. Mel-frequency cepstral coefficient vectors were used to provide an estimate of the vocal tract filter. Meanwhile dynamic time warping was used to detect the nearest recorded voice with appropriate global constraint. The global constraint was used to set a valid search region because the variation of the speech rate of the speaker was considered to be limited in a reasonable range which meant that it could prune the unreasonable search space. The algorithm was tested on speech samples that were recorded as part of a Malay corpus. The results showed that the algorithm managed to recognize almost 80.5% of the Malay digits for all recorded words. The addition of a RLS noise canceller in the preprocessing stage increased the accuracy to 94.1%.
Plurality voter is one of the commonest voting methods for decision making in highly-reliable applications in which the reliability and safety of the system is critical. To resolve the problem associated with sequential plurality voter in dealing with large number of inputs, this paper introduces a new generation of plurality voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. The asymptotic analysis of the new proposed algorithm has demonstrated that it has a time complexity of O(log n) which is less than time complexity of sequential plurality algorithm, i.e. O (n log n).