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Many Mandarin Chinese learners, especially those whose mother tongue’s phonological system differs significantly from Chinese phonological system, find it challenging to learn pronunciation of Chinese phonemes. Yet pronunciation training in language class settings is limited. It is therefore essential to develop computeraided training system to help learners practice Chinese pronunciation without teacher’s assistance. In this article I introduce a prototype of Chinese pronunciation training system that specifically focuses on phoneme substitution errors related to aspiration of consonants. I describe feature extraction process based on multiresolution cochleagram (MRCG), a psychoacoustic model of basilar membrane excitation pattern, and architecture of recurrent neural network (RNN) used for mispronounced phonemes detection. The system achieves 96.12% and 98.58% accuracy rate in detecting phoneme substitution errors and determining aspiration length respectively. Proposed system may be particularly useful for learners of Slavic and Romance origin, since in their mother tongues aspiration is not a distinctive feature.
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