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PLASER: Pronunciation Learning via Automatic Speech Recognition (2003)

Abstract
PLASER is a multimedia tool with instant feedback designed to teach English pronunciation for high-school students of Hong Kong whose mother tongue is Cantonese Chinese. The objective is to teach correct pronunciation and not to assess a student’s overall pronunciation quality. Major challenges related to speech recognition technology include: allowance for non-native accent, reliable and corrective feedbacks, and visualization of errors. PLASER employs hidden Markov models to represent position-dependent English phonemes. They are discriminatively trained using the standard American English TIMIT corpus together with a set of TIMIT utterances collected from “good ” local English speakers. There are two kinds of speaking exercises: minimal-pair exercises and word exercises. In the word exercises, PLASER computes a confidence-based score for each phoneme of the given word, and paints each vowel or consonant segment in the word using a novel 3-color scheme to indicate their pronunciation accuracy. PLASER was used by 900 students of grade 7 and 8 over a period of 2–3 months. About 80 % of the students said that they preferred using PLASER over traditional English classes to learn pronunciation. A pronunciation test was also conducted before and after they used PLASER. The result from 210 students shows that the students ’ pronunciation skill was improved. (The statistics is significant at the 99 % confidence level.)

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.10.3860
Source http://acl.ldc.upenn.edu/W/W03/W03-0204.pdf
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Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Type text
Language English
Relation 10.1.1.49.2776, 10.1.1.21.3288, 10.1.1.17.7948, 10.1.1.8.4690, 10.1.1.101.148, 10.1.1.62.321