Syllable-based Method Of Tone Recognition For Chinese Continuous Speech

Tone is one of primary properties for Chinese. Its functions are listed as the following: constructing words, distinguishing semantic and improving expression effect. It is important to speech recognition, speech synthesis and natural language understanding.In the recent years large progress has been made in speech auto-recognition; many voice speech systems have been developed. Now research on voice recognition turns to large vocabulary speaker-independent continuous speech recognition and natural language understanding. Tone information isn抰 basically used in current Chinese speech recognition system, study on tone recognition is limited to tone recognition of isolated-word and multi-syllabic word, and research on tone patterns and tone recognition for Chinese continuous speech is little.In this dissertation a syllable-based method of tone recognition for continuous speech is proposed. This method includes the following procedures: syllable segmentation, pitch detection, feature extraction, tone pattern analysis, and tone recognition. Our research is show as follows:(1) Syllable segmentation in continuous speech. Syllable is determined as tone recognition unit in this thesis, so syllable segmentation must be done. Syllable segmentation in continuous speech is very difficult. In accordance with chaotic essence of speech signals, syllable segmentation in continuous speech is researched by fractal theory. An approach of syllable segmentation using variance fractal dimension is proposed, its performance is analyzed in detail. The method can discriminate between voiced and unvoiced, between surd and sonant, but it can hardly discriminate between sonant. According to difference of speech waveform between transition segment and non-transition segment, dividing between sonant is researched using waveform cross correlation. A method of syllable segmentation is presented based on waveform cross-correlation.(2) Pitch detection of speech signals. Mandarin tone is the patterns of pitch variation, so it may be acquired by pitch extraction. Many methods of pitch detection are developed so far, in this thesis the pitch detector using waveform transform is adopted. According to the problem appearing in pitch extraction experiment, a novel algorithm of pitch detection is presented. The pitch points in speech signal exhibit local maximum across several consecutive dyadic scales, and their positions are similar, so the improved approach selects pitch points by vote strategy, not by traditional method. Procedure of the new algorithm is as follows: (i) calculating the wavelet transformIII2Abstractacross 5 (or 3) consecutive scales; (ii) choosing pitch points by vote strategy; (iii) checking pitch points; (IV) relocation of pitch points.(3)Feature extraction in tone recognition. Feature extraction is a basic problem in pattern recognition. Valid feature can reflect important information of pattern, and decrease computation and error recognition rate. Mandarin tone is characterized for tone level and tendency of pitch curve, so head-tail difference and relative tone level rate are determined as tone features for Chinese tn-syllable word; head-tail difference and tone level at the beginning of syllable are determined as tone features of syllable in continuous speech.(4)Tone pattern analysis. Tone characteristics of syllable in continuous speech have lager variation than original tone characteristic under the influence of its preceding and posterior syllable, so tone patterns is more complicated, and have only basic characteristic of Chinese tone. Tone patterns and its variation rules are important to tone recognition for continuous speech. In this dissertation tone patterns of disyllabic word and isolated-word are introduced, tone patterns for tn-syllabic word are analyzed in detail. Tone patterns for continuous speech are researched based on the foregoing work.(5)Selection and design of tone recognition module. Tone patterns of syllable in continuous speech...