Connected word recognition using a syntax-directed dynamic programming temporal alignment procedure

In this paper we describe a system for connected word recognition in which a sentence in a formal language, uttered without pauses between words, is recognized by finding the grammatically well formed sequence of isolated word templates to which its distance is least. This is accomplished by means of a single monolithic algorithm in which temporal registration, segmentation and grammatical analysis are performed simultaneously. The algorithm is a syntax-directed version of the level building dynamic time warping algorithm of Myers and Rabiner. A test was conducted on a total of 208 sentences comprising 1781 words and spoken by two male and two female speakers. The sentences were composed from a 127 word vocabulary according to a moderately complex grammar and semantic structure appropriate to an airline information and reservation task. Test results revealed a 13% sentence error rate and a 6% word error rate.