This paper aims at effectively identifying common English mispronunciations by Mandarin speakers and incorporating this knowledge into language learning software to improve the learner's accented English. For this purpose, English and Mandarin multi-channel EMA articulatory datasets collected from native English and native Mandarin speakers respectively have been used to uncover cross-linguistic distinctions. The Procrustes based speaker normalization is used to eliminate the variability which comes from speaker-specific vocal-tract anatomies and other individual biomechanical properties. Then the English phonemes missing from Mandarin and their Mandarin confusing equivalents are identified using phonological knowledge. These English and Mandarin phoneme pairs may be hard to distinguish in acoustics, but by extracting useful information from the changing on tongue positions and shapes of the lips while speaking can be good cross linguistic phoneme level comparison metrics both empirical and quantified. With this method, the same analysis can be done between languages, or different accents within the same language in the future and this knowledge can also be incorporated into language learning software.

Index Terms: mispronunciation, articulatory data, cross linguistic comparison