An Empirical Study of Arabic Continuous Speech Recognition Perfomance

EasyChair Preprint 82

Abstract

Although considerable research has been devoted to English speech recognition, rather less attention has been paid to Arabic speech recognition. The Arabic language is one of the most commonly used languages worldwide that is in need for accurate audio to text converters. In this paper, we evaluate the recognition performance of the Arabic continuous speech using Soundflower Mac utility. That is, Soundflower was employed as a speaker-independent continuous speech recognition system to evaluate the word error rate (WER) and the accuracy of the Arabic speech. The study also contains a comparative study of the speech recognition performance for male and female native speakers. The experiments conducted using a broadcast news modern standard Arabic (MSA) speech corpus of 2.63 hours (10 male and 10 female speakers). The experimental results show that the accuracy is 54.02 %, and the accuracy of the male and female speakers is almost same.

Keyphrases: Arabic, Soundflower, corpus, recognition, speech

@booklet{EasyChair:82,
  author    = {Fawaz Al-Anzi and Dia Abuzeina},
  title     = {An Empirical Study of Arabic Continuous Speech Recognition Perfomance},
  howpublished = {EasyChair Preprint 82},
  year      = {EasyChair, 2018}}