This paper presents our recent work on the development of a tonal Articulatory Feature (AF) for Mandarin and its application to conversational LVCSR. Motivated by the theory of Mandarin phonology, eight features for classi-fying the acoustic units and one feature for classifying the tone are investigated and constructed in the paper, and the AF-based tandem approach is used to improve speech recognition performances. With this Mandarin AF set, a significant relative reduction on Character Error Rate is obtained over the baseline system using the standard acoustic feature, and the comparison between the ASR systems based on AF classifiers with and without the tonal feature demonstrates that the system with the tonal feature achieves better performances further.
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