Tone recognition of polysyllabic words in Mandarin speech - Liu, L.-C.; Yang, W.-J.; Wang, H.-C.; Chang, Y.-C. (Elsevier)
This paper presents a method for the recognition of lexical tones in Mandarin speech based on vector quantization and hidden Markov models. A Kay Visi-Pitch 6087DS is used to extract the fundamental frequency (F"0) contour. The features for the recognition of lexical tones are derived from an F"0 contour within the voiced part of a syllable. Markov models are generated for the four monosyllabic tones and for 15 disyllabic tone pairs based on these derived features. A Viterbi algorithm is applied to find the probability scores of a test tone scored by the models during the recognition phase. In speaker-independent tone recognition experiments, the average recognition rate was 97.9% for isolated monosyllabic words, 92.9% for disyllabic words, and 91.0% for trisyllabic words. The decline comes from the tone variation and the coarticulation between syllables.
http://dx.doi.org/10.1016/0885-2308(89)90021-1
Keywords: E; SQ-SU