Word Hypothesization in Continuous Speech Recognition

Abstract

In this work, we propose the FUB point of view about the word hypothesization in the context of an Automatic Continuous Speech Recognition System. Our starting idea is the impossibility of the modeling the recognition as a sequential process: it is necessary to design an efficient device to locate the words in the continuous context in which they are embeded. We present a quick review of our current efforts on the procedural definition of the Word Hypothesizer and its iteration with a syntactical parsing system developed in our laboratory. We would put some emphasis on the analogy between the word lattice, the output of the word hypothesizer, and the chart, the working data structure of the parser. They are both defined as directed graphs giving the alternate representations — at lexical and at syntactical levels — of input portions. This analogy is the basis of the interaction: the word lattice can be directly mapped into the chart and this becomes the media for information communications among components.