A phone recognizer helps to recognize words better

For most speech recognition systems dynamic features are the only way to incorporate temporal context into the output distributions of the HMM. In this paper we propose an efficient method to utilize a large context in the recognition process. State scores of a phone recognizer which runs in parallel to the word recognizer are computed. Integrating these scores in the HMM of the word recognizer makes their output densities context-dependent. The approach is evaluated on a set of spontaneous utterances which have been recorded with our spoken dialogue system. A significant reduction of the word error rate has been achieved.