A Single Pass Heuristic Search for Segmental Speech Recognizers

The continuous speech recognition problem is usually modeled as a search for the best path in a network of transitions between states. A full search can be very expensive in terms of computation and storage requirements. By adopting a segment based rather than a frame based approach, one can already obtain a reduction of these requirements, but this may still be insuucient to allow for real time recognition. For our segment based Neural Network / Dynamic Programming hybrid, we have therefore developed a heuristic search method performing the search in a single forward pass. The key problem was to identify a suitable heuristic function which estimates the score of the best path yet to be determined. We found that a simple heuristic function taking into account an average path score per segment, does very well. Even if the admissible loss in recognition accuracy is kept small, our heuristic search method outperforms a traditional Viterbi beam search algorithm.