2019
DOI: 10.1016/j.specom.2019.10.005
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Golden speaker builder – An interactive tool for pronunciation training

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Cited by 37 publications
(31 citation statements)
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“…Feedback may be provided by teachers or, less costly but not yet fully accurate, computer-assisted learning programs [43]. Interestingly, research on computer-assisted training suggested that learners benefit more from listening to their own, through speech synthesis corrected, productions than from a native model (e.g., [44,45]). A potential reason for this may be that the mental target model they have developed is also shaped by their own accent, so that a comparison with another speaker does not help detecting errors and accented pronunciation.…”
Section: Discussionmentioning
confidence: 99%
“…Feedback may be provided by teachers or, less costly but not yet fully accurate, computer-assisted learning programs [43]. Interestingly, research on computer-assisted training suggested that learners benefit more from listening to their own, through speech synthesis corrected, productions than from a native model (e.g., [44,45]). A potential reason for this may be that the mental target model they have developed is also shaped by their own accent, so that a comparison with another speaker does not help detecting errors and accented pronunciation.…”
Section: Discussionmentioning
confidence: 99%
“…The concept of "foreign pronunciation culture" was firstly introduced into methodology terminological apparatus by V. V. Buzhinskij in relation to teaching students at primary level of education and later to training linguists-teachers. The problem of teaching pronunciation has received a wide coverage in a number of foreign studies (Cimenli, 2015;Ding et al, 2019;Liakin et al, 2017;Martinsen & Alvord, 2012;Mroz, 2018;Munro, 2008;Pawlak & Szyszka, 2018;Shamat, 2019).…”
Section: Methodsmentioning
confidence: 99%
“…The past 30 years have witnessed evolutionary and farreaching advances in the field of L2 pronunciation, including establishment of the intelligibility principle (Munro and Derwing, 1995;Murphy, 2014), development of a holistic approach acknowledging the importance of both segmental and suprasegmental features (Anderson-Hsieh et al, 1992;Derwing et al, 1998;Levis and Levis, 2018), and development of technologies such as speech visualization (Levis and Pickering, 2004), automated speech recognition (ASR) (Cucchiarini and Strik, 2018) and speech synthesis (Ding et al, 2019).…”
Section: Introductionmentioning
confidence: 99%