الفهرس 
INTRODUCTION AND HISTORICAL REVIEWOnly 14 pages are availabe for public view
 |  | from | 254 |  |  |
| | | from | 254 | | |
Abstract
The main goal of Automatic Speech Recognition (ASR) is to develop techniques and systems that enable computers to accept speech as input. There are many approaches to ASR. The main approaches are template-based, knowledge-based, and stochastic-based approaches. There are other new approaches, which are Artificial Neural Network (ANN), and fuzzy logic. The proposed speech recognition system, which is the main contribution of this work, uses Fuzzy measure to design hybrid Fuzzy HMM Arabic recognition system. The technique is based on a novel Hidden Markov Model based on fuzzy logic and fuzzy integral theory. In this method, the fuzzy integral is used to relax one of the two assumptions that one had with the classical HMM. The traditional HMM and the proposed Fuzzy HMM systems were implemented by computer simulation and a performance comparison was carried out. It is noticed that, there are some improvements in recognition accuracy in case of the Fuzzy HMM (FHMM) system over the classical HMM recognition system. The FHMM recognition system accuracy varies from 93.36% to 98.36% depending on the data set used whereas the classical HMM’ accuracy varies from 91.27% to 94.60% for the same data sets.