Introduction to Arabic Speech Recognition Using CMUSphinx System

TL;DR

This paper explores adapting the open-source CMU Sphinx speech recognition system for Arabic, demonstrating its potential for building an Arabic ASR system using Hidden Markov Models.

Contribution

It introduces a novel approach to develop an Arabic speech recognition system based on CMU Sphinx, highlighting its adaptability to Arabic voice recognition.

Findings

Successful adaptation of CMU Sphinx for Arabic speech recognition

Demonstrated the system's potential for large-vocabulary, speaker-independent recognition

Showed feasibility of using open-source tools for Arabic ASR development

Abstract

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.