Interpretation of iconic utterances based on contents representation: Semantic analysis in the PVI System - Archive ouverte HAL Access content directly
Journal Articles Natural Language Engineering Year : 1998

Interpretation of iconic utterances based on contents representation: Semantic analysis in the PVI System

Abstract

This article focuses on the need for technological aid for agrammatics, and presents a system designed to meet this need. The field of Augmentative and Alternative Communication (AAC) explores ways to allow people with speech or language disabilities to communicate. The use of computers and natural language processing techniques offers a range of new possibilities in this direction. Yet AAC addresses speech deficits mainly, not linguistic disabilities. A model of aided AAC interfaces with a place for natural language processing is presented. The PVI system, described in this contribution, makes use of such advanced techniques. It has been developed at Thomson-CSF for the use of children with cerebral palsy. It presents a customizable interface helping the disabled to compose sequences of icons displayed on a computer screen. A semantic parser, using lexical semantics information, is used to determine the best case assignments for predicative icons in the sequence. It maximizes a global value, the ``semantic harmony'' of the sequence. The resulting conceptual graph is fed to a natural language generation module which uses Tree Adjoining Grammars (TAG) to generate French sentences. Evaluation by users demonstrates the system's strengths and limitations, and shows the ways for future developments.
Fichier principal
Vignette du fichier
jnle97.pdf (433.82 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-00329167 , version 1 (10-10-2008)

Identifiers

Cite

Pascal Vaillant. Interpretation of iconic utterances based on contents representation: Semantic analysis in the PVI System. Natural Language Engineering, 1998, 4 (1), pp.17-40. ⟨10.1017/S1351324997001836⟩. ⟨hal-00329167⟩
60 View
110 Download

Altmetric

Share

Gmail Facebook X LinkedIn More