MODELING SPEECH REPAIRS AND INTONATIONAL PHRASING TO IMPROVE SPEECH RECOGNITION

The spontaneous speech events of speech repairs and intonational phrasing cause disruptions in the local context, and this disruption prevents traditional language models from being able to properly predict the words in the vicinity of these events. The solution is to use a language model that can account for these spontaneous speech events. In this paper, we use such a model to rescore word graphs. This gives a small but significant decrease in the word error rate of 1.2%, in addition to an improvement of 4.4% from modeling the syntactic role of the words. Furthermore, as modeling of spontaneous speech events improves, word recognition results should also improve.