Title :
An NN based tone classifier for Cantonese
Author :
Lee, Tan ; Ching, P.C. ; Chan, L.W. ; Mak, Brian
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Abstract :
Chinese language is a typical monosyllabic tonal language. Tone identification is undoubtedly an essential component in the speech recognition problem of Chinese, specifically for the Cantonese dialect which is well known of being very rich in tones. This paper presents an efficient method for tone classification of isolated Cantonese syllables. Several suprasegmental feature parameters for tone identification are extracted from the voiced portion of each recorded utterance and then fed into a multilayer neural network classifier. Using a large vocabulary containing 234 distinct syllables, the system performance for single-speaker and multispeaker cases are found to be 89% and 87% respectively.
Keywords :
multilayer perceptrons; pattern classification; speech recognition; Cantonese; Chinese; monosyllabic tonal language; multilayer neural network classifier; speech recognition; suprasegmental feature parameters; tone classification; tone identification; Computational complexity; Data mining; Feature extraction; Multi-layer neural network; Natural languages; Neural networks; Speech recognition; System performance; Tongue; Vocabulary;
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
DOI :
10.1109/IJCNN.1993.713914
