My Pronunciation Coach: Improving English pronunciation with an automatic coach that listens

Cucchiarini, Catia; Nejjari, Warda; Strik, Helmer

doi:10.1515/cercles-2011-0024

Cited by 8 publications

(4 citation statements)

References 6 publications

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“…However, research has established a direct link between a speaker’s pronunciation proficiency and their overall L2 communication competence ( Offerman and Olson, 2016 ; Bashori et al, 2022 ). To facilitate effective pronunciation acquisition, timely and personalized feedback is crucial after students deliver their utterances ( Cucchiarini et al, 2012 ). Yet, providing individualized remedial feedback to all students by FL instructors can be arduous, expensive, and impractical, particularly within the L2 classroom setting ( Cucchiarini et al, 2012 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…To facilitate effective pronunciation acquisition, timely and personalized feedback is crucial after students deliver their utterances ( Cucchiarini et al, 2012 ). Yet, providing individualized remedial feedback to all students by FL instructors can be arduous, expensive, and impractical, particularly within the L2 classroom setting ( Cucchiarini et al, 2012 ). It requires not only an understanding of specific sounds but also the ability to produce those sounds, which necessitates significant teaching and feedback efforts ( McCrocklin, 2016 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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The impact of automatic speech recognition technology on second language pronunciation and speaking skills of EFL learners: a mixed methods investigation

Sun

2023

Front. Psychol.

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IntroductionThis study employed an explanatory sequential design to examine the impact of utilizing automatic speech recognition technology (ASR) with peer correction on the improvement of second language (L2) pronunciation and speaking skills among English as a Foreign Language (EFL) learners. The aim was to assess whether this approach could be an effective tool for enhancing L2 pronunciation and speaking abilities in comparison to traditional teacher-led feedback and instruction.MethodsA total of 61 intermediate-level Chinese EFL learners were randomly assigned to either a control group (CG) or an experimental group (EG). The CG received conventional teacher-led feedback and instruction, while the EG used ASR technology with peer correction. Data collection involved read-aloud tasks, spontaneous conversations, and IELTS speaking tests to evaluate L2 pronunciation and speaking skills. Additionally, semi-structured interviews were conducted with a subset of the participants to explore their perceptions of the ASR technology and its impact on their language learning experience.ResultsThe quantitative analysis of the collected data demonstrated that the EG outperformed the CG in all measures of L2 pronunciation, including accentedness and comprehensibility. Furthermore, the EG exhibited significant improvements in global speaking skill compared to the CG. The qualitative analysis of the interviews revealed that the majority of the participants in the EG found the ASR technology to be beneficial in enhancing their L2 pronunciation and speaking abilities.DiscussionThe results of this study suggest that the utilization of ASR technology with peer correction can be a potent approach in enhancing L2 pronunciation and speaking skills among EFL learners. The improved performance of the EG compared to the CG in pronunciation and speaking tasks demonstrates the potential of incorporating ASR technology into language learning environments. Additionally, the positive feedback from the participants in the EG underscores the value of using ASR technology as a supportive tool in language learning classrooms.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

The impact of automatic speech recognition technology on second language pronunciation and speaking skills of EFL learners: a mixed methods investigation

Sun

2023

Front. Psychol.

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“…As a result, attempts are being made at finding alternative, sustainable solutions that can guarantee the amount of care that is required for dysarthria patients in addition to or even without face-to-face sessions [6,7]. In analogy to applications for pronunciation improvement in second language learning, [8,9,10], computer-based systems that employ ASR technology can be used to provide dysarthric patients with more robust and focused practice. A compounding problem however is that progress in these patients is slow, which is likely to reduce their motivation to practice.…”

Section: Introductionmentioning

confidence: 99%

An ASR-Based Interactive Game for Speech Therapy

Ganzeboom¹,

Yılmaz²,

Cucchiarini³

et al. 2016

7th Workshop on Speech and Language Processing for Assistive Technologies (SLPAT 2016)

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The demand for intensive and costly speech therapy to patients impaired by communicative disorders can potentially be alleviated by developing computer-based systems that provide automatized speech therapy in the patient's home environment. In this paper we report on research aimed at developing such a system that combines serious gaming with automatic speech recognition (ASR) technology to provide computer-based therapy to dysarthric patients. The aim of the serious gaming environment is to increase the patients' motivation to practice, which tends to decrease over time with conventional speech therapy, as progress in dysarthric patients is often slow. Additionally, some speech exercises (e.g. drills) are not particularly motivating due to their repetitive nature. The ASR technology is aimed at providing feedback on speech quality during training to improve speech intelligibility. Different types of acoustic models were trained on normal speech of adults and elderly people, and tested on dysarthric speech. The results show that speaker-adaptive training and Deep Neural Networks (DNN)-based acoustic models substantially improve the performance of ASR in comparison to traditional GMM-HMM-based methods. In this specific case, the ASR-based game is developed to provide speech therapy to dysarthric patients, but this approach can be adapted for use in other types of communicative disorders.

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“…fáil ar inneall aitheanta cainte beifear in ann tosú ar chlár a fhorbairt chun fuaimniú na bhfoghlaimeoirí a cheartú agus a chleachtadh (Cucchiarini et al, 2012). Osclófar na doirse chomh maith chun go mbeidh an foghlaimeoir ábalta comhrá ceart ó bhéal a dhéanamh leis an ríomhaire.…”

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Foghlaim ríomhchuidithe teanga-chliste agus teicneolaíocht na hurlabhra: Féidearthachtaí do theagasc/d’fhoghlaim na Gaeilge

Chiaráin

2020

TEANGA

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Tá an córas sintéiseach téacs-go-hurlabhra, ABAIR (www.abair.ie), á fhorbairt sa tSaotharlann Foghraíochta agus Urlabhra i gColáiste na Tríonóide le roinnt blianta anuas agus tá na guthanna sintéiseacha ar fáil anois sna trí mhórchanúint – Canúint na Mumhan (baineann agus fireann), Canúint Connacht (fireann) agus Canúint Uladh (baineann). Tá obair thaighde ar siúl sa tSaotharlann le blianta beaga anuas chun féachaint ar na feidhmeanna ar féidir a bhaint as na guthanna seo. Tá an páipéar seo dírithe ar an úsáid a d'fhéadfaí a bhaint astu i réimse Fhoghlaim Ríomhchuidithe Teangacha-Chliste (FRT-Chliste) agus go háirithe ar an úsáid a d'fhéadfaí a bhaint astu i bhforbairt ardán a cheadódh don fhoghlaimeoir idirghníomhaíocht phearsanta a dhéanamh leis an ríomhaire, rud a chabhródh le foghlaim fhéinriartha na Gaeilge. Léirítear féidearthachtaí na teicneolaíochtaí seo i gcomhthéacs an ardáin phíolótaigh, An Scéalaí, atá á fhorbairt faoi láthair. Text-to-speech synthesis systems are being developed as part of the ABAIR initiative (www.abair.ie), in the Phonetics and Speech Laboratory in Trinity College Dublin. Synthetic voices are now available in the three major dialects - Munster (female and male), Connacht (male) and Ulster (female). This paper gives an overview of the Irish synthetic voices and focuses on their use in the context of Intelligent Computer-Assisted Language Learning (iCALL) and in particular their use in the development of interactive language learning platforms for the self-directed learning of Irish. The potential of this technology is demonstrated in the context of a new iCALL platform, An Scéalaí (‘the Storyteller’), currently under development.

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My Pronunciation Coach: Improving English pronunciation with an automatic coach that listens

Cited by 8 publications

References 6 publications

The impact of automatic speech recognition technology on second language pronunciation and speaking skills of EFL learners: a mixed methods investigation

The impact of automatic speech recognition technology on second language pronunciation and speaking skills of EFL learners: a mixed methods investigation

An ASR-Based Interactive Game for Speech Therapy

Foghlaim ríomhchuidithe teanga-chliste agus teicneolaíocht na hurlabhra: Féidearthachtaí do theagasc/d’fhoghlaim na Gaeilge

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