A JOURNAL SUMMARY (12)

The Effect of Automatic Speech Recognition (ASR) EyeSpeak Software on Iraqi Students’ English Pronunciation: A Pilot Study

Lina Fathi Sidig Sidgi (Corresponding author) Universiti Utara Malaysia, College of Arts and Sciences, 06010 Sintok, Kedah Malaysia E-mail: lheart41@yahoo.com

Ahmad Jelani Shaari School of Education and Modern Languages, Universiti Utara Malaysia, College of Arts and Sciences, 06010 Sintok, Kedah Malaysia E-mail: jelani@uum.edu.my

Advance in Language and Literary studies

Australian International Academic Center, Australia

In teaching English as a Foreign Language (EFL), the most important aspect teachers should focus on is helping the students to master the pronunciation. Students’ poor pronunciation leads to communication failure and learners suffering from low self-esteem and stress. Using automatic speech recognition (ASR) can help the students to identify the differences between the sounds of their mother tongue and the target language. The purpose of the study is to investigate the effectiveness of computer-assisted ASR software in teaching English pronunciation to Iraqi students in the Department of English Language at Al-Turath University College, Baghdad, Iraq and to determine whether teaching pronunciation using ASR is more efficient than using traditional methods. In this study, EyeSpeak software is used. The advantages of the software’s features, such as drills, correction and feedback, may help students reduce pronunciation errors related to the transfer of Arabic sounds to their English speech production.

An experimental research project with a pretest-posttest design is conducted over a one-month period in the Department of English at Al-Turath University College in Baghdad, Iraq. The participants are ten first-year college students, randomly selected from the Department of English, aged between sixteen and twenty-one. The instrument employed in this study were the pronunciation teaching material textbook “Better Pronunciation” by J. D. O’Connor, EyeSpeak software as a multimedia pronunciation-teaching tool that includes speech recognition, online-based pronunciation features and sound-distinction training and also pre-test and post-test.

The data was analyzed using t-test to determine whether the difference between the pretest and posttest was significant or not, a Shapiro-Wilk test, and Levene’s test to assess if the homogeneity of variance assumption was met. The findings revealed that there is a significant improvement in students’ English pronunciation in the posttest compared with their pretest scores. This difference indicates that the use of EyeSpeak software in the pronunciation class helps students in their learning process and leads them to produce more accurate English pronunciation. Thus, the use of EyeSpeak software in a pronunciation class can improve students’ English pronunciation and help them to learn more quickly and realize their error.