نتایج جستجو برای: segmental word-level pronunciation errors
تعداد نتایج: 1311075 فیلتر نتایج به سال:
The Effect of Explicit and Implicit Corrective Feedback on Segmental Word-Level Pronunciation Errors
Over the last few years, the realm of foreign language learning has witnessed an abundance of research concerning the effectiveness of corrective feedback on the acquisition of grammatical features, with the study of other target language subsystems, such as pronunciation, being few and far between. In order to bridge this gap, the present study intended to investigate and compare the immediate...
The present study set out to identify the problematic areas of pronunciation among Iranian female EFL learners. Further, this study investigated the relationship between empathy and authentic pronunciation, along with gender as a moderator variable. Comparing segmental features and phonological processes of both languages helped teachers to predict the target errors. To reach such a goa...
To draw EFL teachers’ attention to pronunciation difficulties resulting from L1 phonotactic constraints, this study examined the hypothesis that certain syllable structures could cause more mispronunciation than segmental sounds for Mandarin-speaking EFL learners. A 145-word reading passage was developed with a total of 30 target sounds, which included the problematic syllable structures that e...
the aim of this study has been to find answers for the following questions: 1. what is the effect of immediate correction on students pronunciation errors? 2. what would be the effect of teaching the more rgular patterns of english pronunciation? 3. is there any significant difference between the two methods of dealing with pronuciation errore, i. e., correction and the teaching of the regular ...
We propose a stochastic pronunciation model using an ergodic hidden Markov model (EHMM) of automatically derived acoustic sub-word units (SWU). The proposed EHMM discovers the pronunciation structure inherent in the acoustic training data of a word without any apriori phonetic transcriptions. The EHMM is an HMM of HMMs – its states are SWU HMMs and the state-transitions compose various possible...
The current emphasis in second language teaching lies in the achievement of communicative effectiveness. In line with this approach, pronunciation training is nowadays geared towards helping learners avoid serious pronunciation errors, rather than eradicating the finest traces of foreign accent. However, to devise optimal pronunciation training programmes, systematic information on these pronun...
This paper investigates the connection between intelligibility and pronunciation accuracy. We compare which words in non-native English speech are likely to be misrecognized and which words are likely to be marked as pronunciation errors. We found that only 16% of the variability in word-level intelligibility can be explained by the presence of obvious mispronunciations. In some cases, a word r...
Second Language Comprehensibility Revisited: Investigating the Effects of Learner Background Dustin Crowther The current study investigated first language (L1) effects on listener judgment of comprehensibility and accentedness in second language (L2) speech. The participants were 60 university-level adult speakers of English from four L1 backgrounds (Chinese, Romance, Hindi, Farsi), with 15 spe...
In this paper, we construct context-independent single-path and multi-path syllable models aimed at improved pronunciation variation modelling. We use phonetic transcriptions to define the topologies of the syllable models and to initialise the model parameters, and the Baum-Welch algorithm for the re-estimation of the model parameters. We hypothesise that the richer topology of multi-path syll...
Automatic localization and diagnosis of pronunciation errors for second-language learners of English
An automatic system for detection of pronunciation errors by adult learners of English is embedded in a language–learning package. Four main features are: (1) a recognizer robust to non–native speech; (2) localization of phone– and word–level errors; (3) diagnosis of what sorts of phone–level errors took place; and (4) a lexical– stress detector. These tools together allow robust, consistent, a...
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