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EnglishCentral (https://www.englishcentral.com), which is also available as an app for most Apple and Android devices, is a second language (L2) learning platform aimed at improving various L2 English skills including language use, vocabulary learning, listening, speaking, and pronunciation via a large selection of short videos. It claims to serve as a multimedia resource for low-as well as high-proficiency L2 learners of English with eight different first language (L1) options to use the platform. Users can also choose the topic, skill, or genre they would like to work on (e.g., academic, business, social, media). This graphically attractive, user-friendly, and easy-to-navigate website is an invaluable tool, especially for those L2 English learners who would like to improve their speaking and pronunciation skills and receive instant feedback. The pronunciation component of the website, which will be the main focus of this review, uses a statistically trained intelligibility model (STIM) as opposed to traditional speech recognition technology, which is particularly helpful for self-diagnosis and self-evaluation of pronunciation skills.
Teaching English as a Second or Foreign Language--TESL-EJ, 2022
Speakometer, an online application that provides segmental practice for its users, was built around Chun’s (2012) three pillars, with a strong auditory feature combined with an ASR to provide learners with relevant pronunciation feedback. The application uses an artificial intelligence (AI) algorithm and ASR to rate the user’s spoken English pronunciation. It is targeted for all users who aim to improve their English pronunciation. The users are provided with immediate feedback, which appears on the screen as verbal (e.g., “Very good”), along with the image of a ‘speakometer’ displaying four colors for the rating: red, orange, yellow and green.
2019
The potential benefits of computer-assisted pronunciation teaching (CAPT) include a private, stress-free learning environment; virtually unlimited input; practice at the student’s own pace; individualized, instantaneous feedback through Automatic Speech Recognition (ASR); and visual acoustic and articulatory displays. Regrettably, however, CAPT software does not always measure up to its potential. Furthermore, many L2 teachers and learners are not familiar with the full range of CAPT possibilities and may not be aware of what features to look for in an instructional product. This paper shares a remedy to this problem—a comprehensive set of criteria for analyzing and evaluating CAPT software, websites, and mobile apps. Utilizing an easy-to-use checklist format, as well as Likert-scale and open-response items, this system is designed to guide teachers and learners in evaluating CAPT programs. The Need to Evaluate CAPT Software Today, increasing numbers of language learners and teacher...
Pedagogy: Journal of English Language Teaching, 2021
Nowadays, artificial intelligence (AI) became a special concern in language teaching for the reason that it can assist and enhance language learning for all levels of education. Again, it had beneficial roles for supplementing language teaching like ELSA Speak App one of Automatic Speech Recognition (ASR) used for teaching pronunciation. It studied how students heard, voiced, uttered, vocalized, and asserted the English words in the oral language, but the students often pronounced incorrect words with the result that the uttered words had faulty meaning. This study aimed to carry out English Language Speech Assistant (ELSA) Speak App to improve English language pronunciation skills to higher education learners that were the English Department Students of Nahdlatul Ulama University of Yogyakarta (UNU). The data were collected using a test of pronunciation and interview. The researcher also taught in the classroom. The results showed that ELSA Speak can increase the students‟ pronunciation skills. It can be seen from the average scores obtained from the teaching cycles from two to four in grade. Clearly, ELSA Speak helped the students pronounce diverse words more easily and comprehensively. Also, the available features offered by this app like instant feedback enabled the students to pronounce precisely. In conclusion, ELSA Speak can improve the students‟ pronunciation skills well and effectively. Indeed, it can motivate the students to engage in learning to pronounce.
Zenodo (CERN European Organization for Nuclear Research), 2023
's Faculty of Languages, Literature, and Arts in Kenitra, Morocco. Dr. Anasse has dedicated a significant amount of time in academic research, teaching, and mentoring. Her contributions to the field have brought her widespread acclaim, making her an important member of the university's faculty. Brahim Mrissa : Brahim Mrissa is a Ph.D. student at the English Studies Department at Ibn Tofail University. He is particularly interested in computer-based language learning, syllabus design, and assessment. In addition to his academic pursuits, Brahim is an enthusiastic ESL teacher.
https://ejournal.indo-intellectual.id/index.php/imeij/issue/view/32, 2024
The objective of this initiative is to improve pronunciation fluency in vocational schools by including a British accent. This study utilized the Wilcoxon signed-rank test as a component to collect both quantitative and qualitative data on product moment SPSS. The data was acquired by pronunciation evaluation test and analysis questions. The data employed in this study was gathered from a vocational school consisting of thirty students enrolled in a hospitality industry and cooking programme. The mean test score is 8.00, and the total amount of ranks is 120.00. According to the statistical test output provided, it is referred to as Asymp. The p-value (two-tailed) is 0.001. Based on the test statistics output above, it is known that Asymp. Sig. (2-tailed) has a value of 0.001, because the value of 0.001 is smaller than 0.05, it can be concluded there is a difference between learning outcomes using text transcripts and shadowing BBC Podcasts and those that do not use text transcripts and shadowing BBC Podcasts. The podcast produced by the BBC can enhance language acquisition by improving pronunciation skills, stimulating students' motivation to achieve English competence, and assisting listeners in developing a predominantly British accent.
Issues and Trends in Educational Technology
Hundreds of millions of language learners worldwide use and purchase language software that may not fully support their language development. This review of Rosetta Stone (Swad, 1992), Duolingo (Hacker, 2011), Babbel (Witte & Holl, 2016), and Mango Languages (Teshuba, 2016) examines the current state of second language (L2) pronunciation technology through the review of the pronunciation features of prominent computer-assisted language learning (CALL) software (Lotherington, 2016; McMeekin, 2014; Teixeira, 2014). The objective of the review is: 1) to consider which L2 pronunciation tools are evidence-based and effective for student development (Celce-Murcia, Brinton, & Goodwin, 2010); 2) to make recommendations for which of the tools analyzed in this review is the best for L2 learners and instructors today; and 3) to conceptualize features of the ideal L2 pronunciation software. This research is valuable to language learners, instructors, and institutions that are invested in effective contemporary software for L2 pronunciation development. This article considers the importance of L2 pronunciation, the evolution of the L2 pronunciation field in relation to the language classroom, contrasting viewpoints of theory and empirical evidence, the power of CALL software for language learners, and how targeted feedback of spoken production can support language learners. Findings indicate that the software reviewed provide insufficient feedback to learners about their speech and, thus, have unrealized potential. Specific recommendations are provided for design elements in future software, including targeted feedback, explicit instructions, sophisticated integration of automatic speech recognition, and better scaffolding of language content.
Language Learning in Higher Education, 2012
Individualized tutoring and feedback by trained language instructors are known to be optimal for language learning. Providing them is timeconsuming and costly, however, and therefore not feasible for the majority of language learners. This applies particularly to pronunciation, where corrective feedback should ideally be synchronous, which makes it even more difficult to provide it adequately in the classroom. Recent systems for computer-assisted pronunciation training (CAPT) that make use of automatic speech recognition (ASR) offer new ways of providing tailored feedback on second language pronunciation. In this paper, we present our new project, My Pronunciation Coach, in which we are developing an ASR-based CAPT program that specifically caters to learners of English with Dutch as their mother tongue. The pronunciation coach software uses speech technology algorithms to detect pronunciation errors. Feedback on these errors is given through an interface in an easily understandable manner and remedial exercises are provided accordingly.
This workshop will guide us through the world of suprasegmental features of pronunciation, look at some ways to help our students learn to hear and use intonation & contrastive stress to provide them with access to a greater range of English communication. We will examine practical ways to integrate pronunciation into lessons within a broader framework of current research and latest practices
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