Abstract

In some speech recognition applications, it is reasonable to constrain the search space of a speech recognizer to a large but finite set of sentences. We demonstrate the problem on a spelling task, where the recognition of continuously spelled last names is constrained to 110,000 entries (= 43,000 unique names) of a telephone book. Several techniques to address this problem are compared: recognition without any language model, bigrams, functions to map a hypothesis onto a legal string, n-best lists, and finally a newly developed method which integrates all constraints directly into the search process within reasonable memory and time bounds. The baseline result of 56% string accuracy is improved to 62, 85, 88, and 92%, respectively. To appear in: Proc. IEEE International Conf. on Acoustics, Speech, and Signal Processing, Detroit, USA, May 1995. 1. INTRODUCTION Spelled letter recognition is an essential subtask of many speech recognition systems. Applications include spelling of arbit...

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