Automatic detection of mispronounced phonemes for language learning tools
Automatic detection of mispronounced phonemes for language learning tools
复制标题
语言学习工具自动检测发音错误的音素
DOI：
10.21437/icslp.2000-169
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Johan Vanparys
中科院分区：
文献类型：
--
作者：
Olivier Deroo;C. Ris;S. Gielen;Johan Vanparys
Automatic Speech Recognition (ASR) can be very useful in language learning tools in order to correct mistakes in the pronunciation of foreign words by non-native speakers. Most of the systems integrating ASR proposed on the market are just rejecting or accepting whole words or whole sentences. In this paper, we propose a method to identify the pronunciation errors at the phoneme level. Indeed, mistakes are often predictable and concern a particular subset of phonemes not present in the mother language of the speaker. We describe two different approaches based on the Hybrid HMM/ANN technology. The methodology for the training of the recognizer is discussed, and we describe a new approach where a mixed database is used to train a speech recognition system able to detect pronunciation errors at the phoneme level. Preliminary but promising results have been obtained on the DEMOSTHENES database.
