Language Identification of Mandarin, Holo, and Hakka based on GMM and PPM models
| Autor: | Chung-Ming Tsai, 蔡仲明 |
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| Rok vydání: | 2007 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 95 In this thesis, different models and model structures are studied to identify among the three languages: Mandarin, Holo, and Hakka. Acoustic features are represented as Mel-frequency cepstrum coefficients (MFCC). In addition, Legendre polynomials and discrete cosine transforms (DCT) are used to approximate the pitch contour of a voice segment. For the two kinds of features, Gauussian mixture models (GMM) are constructed respectively. Also, each frame’s feature vector is tokenized in order to construct a prediction by partial matching (PPM) model to modelize the characteristics embedded in a sequence of tokens. According to the models studied, a practical language identification system has been built. In offline tests, identification success rate can reach 97% in average. In initial online (i.e. inputting with a telephone) tests, the system can obtain a success rate of 73% in average. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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