Tone Recognition in Continuous Mandarin Speech

• Main Authors: Yih-Ru Wang, 王逸如
• Other Authors: Sin-Horng Chen
• Format: Others
• Language: en_US
• Published: 1995
• Online Access: http://ndltd.ncl.edu.tw/handle/80549709559690772088

博士 === 國立交通大學 === 電子研究所 === 83 === The characteristics of the tones of Mandarin speech is in general not soley determined by its lexical tonality, but also affected by other factors. In this dissertation, three tone recognizer approaches are studied. First, the HMM-based approach is discussed. Serveral schemes to consider the effects of the coarticulation and the intonation of utterence on tone recogni- tion are proposed. Effectiveness of these schemes were examined by simulation on a multi-speaker database. A recognition rate of 86.62% was archieved. Second, the neural net based approaches are studied. There also consider the coarticulation effect by including the features from neighboring syllables. And, the hidden control neural net(HCNN) and hidden state multi-layer perceptron(HSMLP) are used for compensating the declination effect. Experiment shows 86.72% recognition rate was achieved for a larger database. Last, the approach using a prosodic model to assist tone recognition is studied. A simple recurrent neural net(SRNN) is emploed to model the prosody of an utterance. By using the outputs of the hidden nodes of SRNN to assist an MLP tone recognizer, an improvement on recognition rate from 91.38% to 93.10% was achieved for a single male speaker database.