Showing papers by "Pedro García-Teodoro published in 1997"

A voice activated dialogue system for fast-food restaurant applications.

Abstract: We present a preliminary version of a voice dialogue system suitable to deal with client orders and questions in fast-food restaurants. The system consists of two main sub-systems, namely a dialogue sub-system and a voice interface. The dialogue sub-system is a natural language processing system that may be considered a rule-based expert system, whose behaviour is decided from a recorded dialogue corpus obtained at a real restaurant. In this paper we present a general description of both sub-systems, and focus on knowledge representation, grammar, and module structure of the dialogue sub-system. An introduction to the natural language generation mechanism used is introduced, and future work is mentioned. Finally some conclusions are shown.

STACC: an automatic service for information access using continuous speech recognition through telephone line.

Abstract: This work presents the STACC, Sistema Telefonico Automatico de Consulta de Calificaciones (Automatic Telephone System for Consulting Marks) This system has been developed at our laboratory during 1996 and implements a service through telephone line that allows the students to consult by speech their marks after the exams by means of a simple phone call This experience provided us an interesting point of view about the problems of real applications of speech technology In this work we describe the system and some statistics about the use of STACC by the students are presented

Discriminative feature extraction for speech recognition in noise.

Abstract: Signal representation is crucial for designinga speechrecognizer. The feature extractor selects the information to be used by the classifier to perform the recognition. In noisy environments, the data vectors representing the speech signal are changed and the recognizer performance is degraded by two main facts: (1) the mismatch between the training and the recognition conditions and (2) the degradation of the signal to be recognized. In such a situation, the representation of the speech signal plays an important role. In this paper, we analyze the importance of the representation for speechrecognition in noise. We apply the Discriminative Feature Extraction (DFE) method to optimize the representation. The experiments presented in this work show that the DFE method, which has been successfully applied in clean environments, leads also to improvements of the speech recognizers in noise.