A comparative study of the classification techniques in isolated Mandarin syllable tone recognition
Jiatang Dong, Cen Li · 2011
Tonal languages, such as Chinese, use systematic variations of pitch to distinguish lexical or grammatical meaning. Thus, tone recognition is essential for tonal languages. Typically, tone recognition for isolated syllables involves three major steps: fundamental frequency (F0) detection, feature extraction, and classification. The work compares different techniques for these three steps and to answer the questions: for Mandarin Chinese syllables, what combination of fundamental frequency detection and feature extraction methods best prepare data for classification, and what is the most effective classification method for tone recognition. Three types of F0 detection methods (autocorrelation, cross-correlation and cepstrum), two feature extraction schemes (sampled F0 and average F0, slope and energy from three subsegments), four normalization methods (slope only, 0--100 scaled, z-score and T1 shift), and two classification methods (Support Vector Machine (SVM) and Multilayer Perceptron (MLP)) were experimentally studied using 700 collected data samples.