Several approaches to Chinese dialect identification based on segmental and prosodic features of speech are described in this paper. When using segmental information only, the system performs phonotactic analysis after speech utterances have been tokenized into sequences of broad phonetic classes. The second scheme comprises prosodic models which are trained to capture tone sequence information for individual dialects. Also proposed is a novel approach that examines differences between Chinese dialects at broad phonetic and prosodic levels. These algorithms were evaluated via a multispeaker read-speech mode. Simulation results indicate that the combined use of segmental and prosodic features allows the proposed system to discriminate among three major Chinese dialects spoken in Taiwan with 93.0% accuracy.
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