The Usefulness of Automatic Speech Recognition (ASR) Eyespeak Software in Improving Iraqi EFL Students’ Pronunciation

Abstract

The present study focuses on determining whether automatic speech recognition (ASR) technology is reliable for improving English pronunciation to Iraqi EFL students. Non-native learners of English are generally concerned about improving their pronunciation skills, and Iraqi students face difficulties in pronouncing English sounds that are not found in their native language (Arabic). This study is concerned with ASR and its effectiveness in overcoming this difficulty. The data were obtained from twenty participants randomly selected from first-year college students at Al-Turath University College from the Department of English in Baghdad-Iraq. The students had participated in a two month pronunciation instruction course using ASR Eyespeak software. At the end of the pronunciation instruction course using ASR Eyespeak software, the students completed a questionnaire to get their opinions about the usefulness of the ASR Eyespeak in improving their pronunciation. The findings of the study revealed that the students found ASR Eyespeak software very useful in improving their pronunciation and helping them realise their pronunciation mistakes. They also reported that learning pronunciation with ASR Eyespeak enjoyable.

Elsa Speak App: Automatic Speech Recognition (ASR) for Supplementing English Pronunciation Skills

“…The use of ASR was more effective than the traditional mode in learning to pronounce. Moreover, the (Fathi Sidig Sidgi & Jelani Shaari, 2017) research on the use of ASR in pronunciation class got significant results. It claimed that ASR was very beneficial in supporting the students" pronunciation skills and helping the students appreciate the error and mistakes in sounding words.…”

Learning With Mobile Augmented Reality- and Automatic Speech Recognition-Based Materials for English Listening and Speaking Skills: Effectiveness and Perceptions of Non-English Major English as a Foreign Language Students

“…The use of ASR-based software was reported to develop positive experiences of second language (L2) learners and to enhance their learning effectiveness, motivation and confidence in practicing language (Golonka et al, 2014; Hwang et al, 2020; Li, et al, 2017; Sidgi & Shaari, 2017). English pronunciation by Chinese learners was improved with the application of ASR technology (Evers & Chen, 2021; Li, et al, 2017).…”

Using Automatic Speech Recognition to Facilitate English Pronunciation Assessment and Learning in an EFL Context

“…Another area of ASR technology application is pronunciation assessment, in which learners performcontrolledpronunciationtasks,suchasreadingsentencesaloud,andtheASRsystemdiagnoses pronunciationerrorsbasedonthestudents'performance.Automaticpronunciationassessmentcan reduceL2teachers'workloadofscoringlearners'pronunciationandnarrowdownthepronunciation instructionscopebyaddressinglearners'frequenterrors.Withtheadvancementofspeechmodels, thegapbetweenhumanandmachinescoringhasbeennarrowed.Cheng,Bojja,andChen( 2013) foundahighcorrelation(0.84)betweenhumanandmachinescoringofpronunciation.AnotherASR-supportedspokenEnglishtestingsystem,Versant,demonstratedahighcorrelationof0.88between humanscoringandmachinescoringoflearners'pronunciations (Pearson,2011). AgrowingnumberofresearchstudieshavefocusedondiscoveringtheeffectivenessofASR technologyonpronunciationimprovement (Chun,2012;Elimat&AbuSeileek,2014;Liu&Hung, 2016;Sidgi & Shaari, 2017). Less research attention has been paid to automatic pronunciation assessment,whichholdsgreatpotentialforreducinghumanratingloadandprovidingobjectiveand reliablemeasurementresults.Inaddition,researchinvestigatingthelearners'orteachers'attitudes towards the adoption of ASR-supported pronunciation software as an assessment tool and as a pronunciationlearningtoolisrelativelyunderexplored.…”