A speech understanding system based on statistical representation of semantics
Roberto Pieraccini, Evelyne Tzoukermann, Zakhar Gorelov, J.-L. Gauvain, Esther Levin, C.-H. Lee, Jay G. Wilpon · 1992
An understanding system, designed for both speech and text input, has been implemented based on statistical representation of task specific semantic knowledge. The core of the system is the conceptual decoder, which extracts the words and their association to the conceptual structure of the task directly from the acoustic signal. The conceptual information, which is also used to clarify the English sentences, is encoded following a statistical paradigm. A template generator and an SQL (structured query language) translator process the sentence and produce SQL code for querying a relational database. Results of the system on the official DARPA test are given.>