Predicting gradation of L2 English mispronunciations using crowdsourced ratings and phonological rules
نویسندگان
چکیده
Pedagogically, CAPT systems can be improved by giving effective feedback based on the severity of pronunciation errors. We obtained perceptual gradation of L2 English mispronunciations through crowdsourcing, and conducted quality control utilizing the WorkerRank algorithm to refine the collected results and reach a reliable consensus on the ratings of word mispronunciations. This paper presents our work on modeling the relationship between the phonetic mispronunciations and the actual word ratings. Based on phonological rules representing phonetic mispronunciation productions, we propose two approaches to predict the gradation of word mispronunciations. Reasonable correlation and agreement are found between the human-labeled and machinepredicted gradations for both approaches, which imply that the use of phonological rules in word-level mispronunciation gradation prediction is promising.
منابع مشابه
Developing Speech Recognition and Synthesis Technologies to Support Computer-Aided Pronunciation Training for Chinese Learners of English
Copyright 2009 by Helen Meng Abstract. We describe ongoing research in the development of speech technologies that strives to raise the efficacy of computer-aided pronunciation training, especially for Chinese learners of English. Our approach is grounded on the theory of language transfer and involves a systematic phonological comparison between the primary language (L1 being Chinese) and seco...
متن کاملDeriving salient learners' mispronunciations from cross-language phonological comparisons
This work aims to derive salient mispronunciations made by Chinese (L1 being Cantonese) learners of English (L2 being American English) in order to support the design of pedagogical and remedial instructions. Our approach is grounded on the theory of language transfer and involves systematic phonological comparison between two languages to predict possible phonetic confusions that may lead to m...
متن کاملAutomatic derivation of phonological rules for mispronunciation detection in a computer-assisted pronunciation training system
Computer-Assisted Pronunciation Training System (CAPT) has become an important learning aid in second language (L2) learning. Our approach to CAPT is based on the use of phonological rules to capture language transfer effects that may cause mispronunciations. This paper presents an approach for automatic derivation of phonological rules from L2 speech. The rules are used to generate an extended...
متن کاملAutomatic generation and pruning of phonetic mispronunciations to support computer-aided pronunciation training
This paper presents a mispronunciation detection system which uses automatic speech recognition to support computer-aided pronunciation training (CAPT). Our methodology extends a model pronunciation lexicon with possible phonetic mispronunciations that may appear in learners’ speech. Generation of these pronunciation variants was previously achieved by means of phone-tophone mapping rules deriv...
متن کاملPhonological Feature Based Mispronunciation Detection and Diagnosis Using Multi-Task DNNs and Active Learning
This paper presents a phonological feature based computer aided pronunciation training system for the learners of a new language (L2). Phonological features allow analysing the learners’ mispronunciations systematically and rendering the feedback more effectively. The proposed acoustic model consists of a multi-task deep neural network, which uses a shared representation for estimating the phon...
متن کامل