Chinese all syllables recognition using combination of multiple classifiers

Chinese all syllables recognition is described. Chinese all syllables recognition is divided into base syllable recognition disregarding the tones and 4 tones recognition. For base syllable recognition, we used a combination of two multisegment vector quantization (MSVQ) classifiers based on different features (instantaneous and transitional features of speech). For the tones recognition, the vector quantization (VQ) classifier is first used, and is comparable to a multilayer perceptron (MLP) classifier. Next, a combination of a distortion based classifier (VQ) and a discriminant based classifier (MLP) is proposed. An evaluation has been carried out using the standard Chinese syllable database CRDB, and experimental results have shown that the combined classifiers can improve the recognition performance. The recognition accuracy for base syllable and tones is 96.48% and 99.82% respectively