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This paper presents a method to improve the mispronunciation detection performance for low-resource acoustic model. The 1h speech data is randomly selected from CU-CHLOE to imitate the low-resource non-native English situation. The Tandem feature derived from articulatory based Multi-Layer Perception (MLP) is employed to replace the traditional spectral feature (e.g. PLP). Further, motivated by similar...
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