Improving Computer Based Speech Therapy Using a Fuzzy Expert System

In this paper we present our work about Computer Based Speech Therapy systems optimization. We focus especially on using a fuzzy expert system in order to determine specific parameters of personalized therapy, i.e. the number, length and content of training sessions. The efficiency of this new approach was tested during an experiment performed with our CBST, named LOGOMON

From Fuzzy Expert System to Artificial Neural Network: Application to Assisted Speech Therapy

This chapter addresses the following question: What are the advantages of extending a fuzzy expert system (FES) to an artificial neural network (ANN), within a computer‐based speech therapy system (CBST)? We briefly describe the key concepts underlying the principles behind the FES and ANN and their applications in assisted speech therapy. We explain the importance of an intelligent system in order to design an appropriate model for real‐life situations. We present data from 1‐year application of these concepts in the field of assisted speech therapy. Using an artificial intelligent system for improving speech would allow designing a training program for pronunciation, which can be individualized based on specialty needs, previous experiences, and the child\u27s prior therapeutical progress. Neural networks add a great plus value when dealing with data that do not normally match our previous designed pattern. Using an integrated approach that combines FES and ANN allows our system to accomplish three main objectives: (1) develop a personalized therapy program; (2) gradually replace some human expert duties; (3) use “self‐learning” capabilities, a component traditionally reserved for humans. The results demonstrate the viability of the hybrid approach in the context of speech therapy that can be extended when designing similar applications

Does the Road from Web to Native Really Worth? Academic Timetable Case Study

Abstract: One of the main implicit goal of Information revolution is to transfer knowledge from natural language, familiar for humans, to a language appropriate for computers. Every software application represents a tiny step forward in this complex process. However, although remarkable progress in terms of portability, we are still in the position to write the same application on and on if we want maximum performance and user friendly interface. In this article we analyze two applications for visualization of the academic schedule – web and native (Android) – taking into consideration portability, performance, offered features, and usability. Both applications use the same data and they can be accessed for free in order to interact with academic timetable of “Ștefan cel Mare” University of Suceava. The experimental results address both an objective part (performance and portability) and a subjective part (usability and importance of additional features). These results offer interesting clues regarding what it is important for end user when they interact with an interface application