2007/04/17 by Hassan Satori, H. Satori, Satori, H. +6 · 1 citation
Computer Science · #Algorithms and Data Compression #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2.7 #Natural Language Processing Techniques #Speech Recognition and Synthesis #cs.AI #cs.CL
paper · pdf · doi:10.48550/arxiv.0704.2083
4 pages, 3 figures and 2 tables, was in Information and Communication Technologies International Symposium proceeding ICTIS07 Fes (2007)
arxiv created 2007/04/17 · openalex publication_date 2007/04/17 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper Arabic was investigated from the speech recognition problem point of view. We propose a novel approach to build an Arabic Automated Speech Recognition System (ASR). This system is based on the open source CMU Sphinx-4, from the Carnegie Mellon University. CMU Sphinx is a large-vocabulary; speaker-independent, continuous speech recognition system based on discrete Hidden Markov Models (HMMs). We build a model using utilities from the OpenSource CMU Sphinx. We will demonstrate the possible adaptability of this system to Arabic voice recognition.