Enhancing speech recognition in developing language learning systems for low cost Androids

Jayakumar, A.; Raghunath, Meera; M.S, Sakthipriya; Akhila, S.; Sadanandan, Anuja; Nedungadi, Prema

doi:10.1109/icctict.2016.7514556

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Corrective Feedback In Capt Experiments1

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Cited by 4 publications

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“…On the one hand, some systems use ASR with very simple explicit feedback: HMM scores as feedback [60], [67], [103], right/wrong answers [65], or green (acceptable) / red (unacceptable) answers with words presented in appropriate contexts through audio and text and associated with representative images in case of mispronounced words [107]. In the case of mispronouncing sentences, the system offers to repeat the single mispronounced words [116] or the whole sentence [103], [117].…”

Section: Corrective Feedback In Capt Experimentsmentioning

confidence: 99%

Design and evaluation of mobile computer-assisted pronunciation training tools for second language learning

García¹

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This PhD thesis has been carried out in the ECA-SIMM research group with the Department of Computer Science of the University of Valladolid. My first contact with the research group was when I was finishing my master's degree in Computer Science at the middle of the year 2015. They were looking for one candidate to start researching in foreign pronunciation teaching with speech technology and mobile applications within a research project. I was really interested in what I was doing from the very first day in the laboratory.

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