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Jiang, Yan; Chun, Dorothy – Computer Assisted Language Learning, 2023
This paper examines whether a web-based training on English discourse intonation leads to better spontaneous speech quality for Mandarin Chinese speakers who reside in the U.S. and in China. The four-week fully online training consisted of meta-instruction videos as well as listening and speaking activities, including instant visual pitch contour…
Descriptors: Oral Language, Second Language Learning, Second Language Instruction, English (Second Language)
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Mengtian Chen – Computer Assisted Language Learning, 2024
This article discusses whether digital visual and audio feedback in learners' own voices improves their perception and production of lexical tones in Chinese as a foreign language. Forty-four beginners participated in a four-week training focused on the pronunciation of Mandarin Chinese tones at the word level. Half received digital feedback…
Descriptors: Feedback (Response), Computer Assisted Instruction, Pronunciation Instruction, Mandarin Chinese
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Muzakki Bashori; Roeland van Hout; Helmer Strik; Catia Cucchiarini – Computer Assisted Language Learning, 2024
Speaking skills generally receive little attention in traditional English as a Foreign Language (EFL) classrooms, and this is especially the case in secondary education in Indonesia. A vocabulary deficit and poor pronunciation skills hinder learners in their efforts to improve speaking proficiency. In the present study, we investigated the effects…
Descriptors: Computer Assisted Instruction, Teaching Methods, Audio Equipment, Video Technology
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Dai, Yuanjun; Wu, Zhiwei – Computer Assisted Language Learning, 2023
Although social networking apps and dictation-based automatic speech recognition (ASR) are now widely available in mobile phones, relatively little is known about whether and how these technological affordances can contribute to EFL pronunciation learning. The purpose of this study is to investigate the effectiveness of feedback from peers and/or…
Descriptors: Educational Technology, Technology Uses in Education, Telecommunications, Handheld Devices
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Jingjing Zhu; Xi Zhang; Jian Li – Computer Assisted Language Learning, 2024
Traditional L2 pronunciation teaching puts too much emphasis on explicit phonological knowledge ('knowing that') rather than on procedural knowledge ('knowing how'). The advancement of mobile-assisted language learning (MALL) offers new opportunities for L2 learners to proceduralize their declarative articulatory knowledge into production skills…
Descriptors: Artificial Intelligence, Technology Uses in Education, Pronunciation Instruction, Second Language Instruction
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Evers, Katerina; Chen, Sufen – Computer Assisted Language Learning, 2022
This study examined the difference in adults' pronunciation performance with peer feedback and individual practice when using an automatic speech recognition (ASR) system. The same ASR software was used in both the comparison (n = 31) and the experimental group (n = 33) for 12 weeks. The participants were working adults in Taiwan. During the…
Descriptors: Automation, Computer Assisted Instruction, Speech Communication, Peer Evaluation
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van Doremalen, Joost; Boves, Lou; Colpaert, Jozef; Cucchiarini, Catia; Strik, Helmer – Computer Assisted Language Learning, 2016
The purpose of this research was to evaluate a prototype of an automatic speech recognition (ASR)-based language learning system that provides feedback on different aspects of speaking performance (pronunciation, morphology and syntax) to students of Dutch as a second language. We carried out usability reviews, expert reviews and user tests to…
Descriptors: Case Studies, Speech, Indo European Languages, Second Language Learning
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Liakin, Denis; Cardoso, Walcir; Liakina, Natallia – Computer Assisted Language Learning, 2017
We examine the impact of the pedagogical use of mobile TTS on the L2 acquisition of French liaison, a process by which a word-final consonant is pronounced at the beginning of the following word if the latter is vowel-initial (e.g. peti/t.a/mi = > peti[ta]mi "boyfriend"). The study compares three groups of L2 French students learning…
Descriptors: French, Second Language Learning, Second Language Instruction, Control Groups
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Engwall, Olov – Computer Assisted Language Learning, 2012
Pronunciation errors may be caused by several different deviations from the target, such as voicing, intonation, insertions or deletions of segments, or that the articulators are placed incorrectly. Computer-animated pronunciation teachers could potentially provide important assistance on correcting all these types of deviations, but they have an…
Descriptors: Feedback (Response), Phonetics, Pronunciation, Computer Assisted Instruction
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Patten, Iomi; Edmonds, Lisa A. – Computer Assisted Language Learning, 2015
The present study examines the effects of training native Japanese speakers in the production of American /r/ using spectrographic visual feedback. Within a modified single-subject design, two native Japanese participants produced single words containing /r/ in a variety of positions while viewing live spectrographic feedback with the aim of…
Descriptors: Japanese, English (Second Language), Second Language Instruction, Visual Stimuli
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Ouni, Slim – Computer Assisted Language Learning, 2014
Pronunciation training based on speech production techniques illustrating tongue movements is gaining popularity. However, there is not sufficient evidence that learners can imitate some tongue animation. In this paper, we argue that although controlling tongue movement related to speech is not such an easy task, training with visual feedback…
Descriptors: Pronunciation Instruction, Pretests Posttests, Feedback (Response), Psychomotor Skills
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Luo, Beate – Computer Assisted Language Learning, 2016
This study investigates a computer-assisted pronunciation training (CAPT) technique that combines oral reading with peer review to improve pronunciation of Taiwanese English major students. In addition to traditional in-class instruction, students were given a short passage every week along with a recording of the respective text, read by a native…
Descriptors: Computer Assisted Instruction, Pronunciation, Second Language Instruction, Peer Evaluation
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Golonka, Ewa M.; Bowles, Anita R.; Frank, Victor M.; Richardson, Dorna L.; Freynik, Suzanne – Computer Assisted Language Learning, 2014
This review summarizes evidence for the effectiveness of technology use in foreign language (FL) learning and teaching, with a focus on empirical studies that compare the use of newer technologies with more traditional methods or materials. The review of over 350 studies (including classroom-based technologies, individual study tools,…
Descriptors: Educational Technology, Teaching Methods, Second Language Instruction, Second Language Learning
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Engwall, Olov; Balter, Olle – Computer Assisted Language Learning, 2007
The aim of this paper is to summarise how pronunciation feedback on the phoneme level should be given in computer-assisted pronunciation training (CAPT) in order to be effective. The study contains a literature survey of feedback in the language classroom, interviews with language teachers and their students about their attitudes towards…
Descriptors: Second Language Learning, Second Language Instruction, Pronunciation, Language Teachers