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IEEE MULTIDISCIPLINARY ENGINEERING EDUCATION MAGAZINE, VOL. 3, NO. 3, SEPTEMBER 2008 1558-7908 2008 IEEE Education Society Students Activities Committee (EdSocSAC)
 

Summary: IEEE MULTIDISCIPLINARY ENGINEERING EDUCATION MAGAZINE, VOL. 3, NO. 3, SEPTEMBER 2008
1558-7908 2008 IEEE Education Society Students Activities Committee (EdSocSAC)
http://www.ieee.org/edsocsac
Speech Recognition using Artificial Neural
Networks and Hidden Markov Models
Mohamad Adnan Al-Alaoui, Lina Al-Kanj, Jimmy Azar, and Elias Yaacoub
Abstract--In this paper, we compare two different methods for
automatic Arabic speech recognition for isolated words and
sentences. Isolated word/sentence recognition was performed
using cepstral feature extraction by linear predictive coding, as
well as Hidden Markov Models (HMM) for pattern training
and classification. We implemented a new pattern
classification method, where we used Neural Networks trained
using the Al-Alaoui Algorithm. This new method gave
comparable results to the already implemented HMM method
for the recognition of words, and it has overcome HMM in the
recognition of sentences. The speech recognition system
implemented is part of the Teaching and Learning Using
Information Technology (TLIT) project which would
implement a set of reading lessons to assist adult illiterates in

  

Source: Al-Alaoui, Mohamad Adnan - Faculty of Engineering and Architecture, American University of Beirut, Lebanon

 

Collections: Engineering