Simultaneous speech segmentation and phoneme recognition using dynamic programming

In this paper a dynamic programming algorithm for simultaneous speech segmentation and phoneme recognition is presented. Given a sequence of samples of an unknown speech pattern and a library of phonemes, this algorithm finds the best phonological match and, with a backtracking step, identifies the phoneme boundaries. This approach is different from a traditional two step process whereby first the phoneme boundaries are determined locally and then speech recognition is performed. Its advantage over the two step process is that incorrect phoneme boundaries due to slurring or sudden changes in the speech are reduced. Unlike other dynamic programming algorithms, it does not lend itself to systolic wavefront processing, hence an alternate parallel algorithm is presented.