Guest Editorial

Machine vision is an exciting part of modern cognitive and computer science with a significant growth in the areas of medical image processing, earth resource inventory, industrial production, automatic navigation and office automation

An Overview of the Slovenian Spoken Dialog System

In the paper we present the modules of the Slovenian spoken dialog system, developed within the joint project in multilingual speech recognition and understanding “Spoken Queries in European Languages” (SQEL-Copernicus-1634). The system can handle spontaneous speech and provide the user with correct information in the domain of air flight information retrieval. The major modules of the system perform word recognition, linguistic analysis, dialog management and speech synthesis. Some results with respect to word accuracy, semantic accuracy and dialog success rate are given, too

Text-to-Speech Synthesis: A Complete System for the Slovenian Language

A text-to-speech system, capable of synthesising continuous Slovenian speech from an arbitrary input text is described. The text-to-speech system is based on the concatenation of basic speech units, diphones, using the TD-PSOLA technique, and no special hardware is required. The input text is transformed into its spoken equivalent by a series of the modules. The modules, constituting the text-to-speech system are described in detail. Special attention is paid to segmental duration determination, where the effect of speaking rate on phone duration is widely studied. Finally, the results of output speech quality assessment are given in terms of acceptability and intelligibility

Semantic Decomposition of Sentences in the System Supporting Flight Services

The paper describes the semantic part of the linguistic analysis of a recognized word hypothesis lattice, as implemented in an information dialogue system, capable of recognizing and understanding Slovenian speech. It describes the new Slovenian speech database from a semantic point of view. Semantic analysis is performed in three different steps: first, parsing of complex temporal expressions; second, parsing of simple noun phrases: this method is used for the departure/arrival location determination and in the third step we are looking for keywords defining the intended question . We propose some templates dealing with timetables, departure and arrival times, airline companies, etc. The different templates compete on each utterance. Finally, the template with the best score generates a database query. Some experimental results of the semantic decomposition are presented

Continuous Speech Recognition by a Network of Hidden Markov Models

This paper gives an overview of the principles of a system for phoneme based, large vocabulary, continuous speech recognition. In particular, the issue of acoustic-phonetic modelling using Hidden Markov Models is addressed.Some experiences of Laboratory for artificial perception at University of Ljubljana in attacking some of these problems is presented

Guest Editorial

The Journal of Computing and Information Technology is pleased to devote a complete issue to a selection of papers presented at the Third Slovenian-German and the Second Workshop of Slovenian Society for Pattern Recognition (SDRV) held in Ljubljana from April 24-26, 1996

An Extended G-Net Model for Knowledge Representation

A new, generalized scheme for knowledge representation of fuzzy timed systems is proposed. The scheme is based on principles of a G-net model. We extended the existing G-net capabilities by the possibility of describing fuzzy defined and time dependent relationships among the system agents.A fuzzy system is described by fuzzy relations. A fuzzy production rule is represented by a fuzzy term and valued by a certainty factor. Possibilities of modeling different types of knowledge are given.Time dependencies in the systems and their representations vary according to the nature of the problems studied and a type of represented knowledge.The represented scheme is capable of a static and a dynamic knowledge representation in a unique framework and enables interaction and coordination of both types of knowledge.Finally, some illustrative examples are given

Fuzzy Expert System for Pattern Recognition

In a pattern recognition environment it is often difficult to capture information in a precise form, and consequently, the knowledge about the recognition domain (problem) may be inexact, incomplete or not reliable. In order to properly represent the knowledge of this kind, fuzzy production rules have been used. In this paper fuzzy Petri nets are used as a knowledge representation scheme in which the fuzzy production rules are applied for describing a fuzzy relation between two propositions. Based on the fuzzy Petri net model of a knowledge base, an efficient algorithm is proposed to perform fuzzy reasoning automatically