| 英文摘要 | Automatic prosody diagnosis is an important part of computer aided language learning and computer-assisted language testing system. This paper focuses on the deep exploration of key issues of prosody diagnosis including stress, tone and intonation in the process of language learning of standard Mandarin based on the analysis of the mainstream methods of current for prosody assessment. The contribution and novelty of this paper are listed as: 1. Proposed the method of diagnosis of stress in Mandarin based on the fusion of super-segmental features including pitch, duration, energy, sub-bands energy based on TEO operator, PLP, the relativity of the stress in utterance is taken into account, also the effectiveness of the different feature are discussed. Experimental results show that the importances of stress features are: duration, sub-bands energy, pitch, energy, PLP. Simultaneously, tone dependent stress model are proposed to improve the performance of the stress detection system, application on real dataset validates its feasibility and effectiveness. 2. Proposed the approach of tone error detection and diagnosis on clustering method of dominant set towards the strong accented single syllable word. For this special application, the cross-correlation between dominant set and human reaches to that of between humans on the real data corpus, and achieves better performance than the traditional k-means based method. Meanwhile, the detection method based on clustering can provide more informative feedbacks denoted by the F0 contours. 3. Towards the issue of tone error detection in strong accented continuous speech, a novel framework and integral system are built based on clustering techniques. For the first time, we carry out the researches on the feasibility and effectiveness from different perspectives with the methods of tone clustering for diagnosis based on Unitone, Bitone and Tritone, besides, the word segmentation is also introduced. To deal with the problem of sparse data on Tritone, decision tree based approach is utilized for collecting the contextual information, experimental results show that it achieves more satisfying performance. Compared with traditional tone error detection method, one distinct advantage lies in that more precisely feedbacks can be provided in the form of F0 contour in the language learning process. Experimental results show that the proposed method is feasible and effectiveness. 4. Build an integral subsystem to carry out int... |
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