PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

On the use of finite state transducers for semantic interpretation
Christian Raymond, Fréderic Béchet, Renato De Mori and Geraldine DAMNATI
Speech Communication Volume in press, Number in press, 2005.

Abstract

A spoken language understanding (SLU) system is described. It generates hypotheses of conceptual constituents with a translation process. This process is performed by finite state transducers (FST) which accept word patterns from a lattice of word hypotheses generated by an Automatic Speech Recognition (ASR) system. FSTs operate in parallel and may share word hypotheses at their input. Semantic hypotheses are obtained by composition of compatible translations under the control of composition rules. Interpretation hypotheses are scored by the sum of the posterior probabilities of paths in the lattice of word hypotheses supporting the interpretation. A compact structured n-best list of interpretation is obtained and used by the SLU interpretation strategy.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Speech
ID Code:1820
Deposited By:Fréderic Béchet
Deposited On:29 November 2005