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TV Commercials play an important role in our lives, and automatic commercial detection is very useful in TV video analysis. Most of previous works focus on visual and audio features of commercial, while ignoring the information of distributions of commercial blocks in different program types and broadcast times. In this paper, we propose a novel method to fuse visual, audio features and global characteristics...
In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine...
Automatic assessment of word stress error is an integral part for oral language grading system. However, problems that the property of vowels depends on its context information and the data sparseness of different vowel class are yet to be solved. This paper shall briefly introduce a hybrid method consisting of both traditional prosodic features and proposed context dependent strategies. In classification...
This paper presents a new approach that uses linguistic knowledge and pronunciation space for automatic detection of typical phone-level errors made by non-native speakers of mandarin. Firstly, linguistic knowledge of common learner mistakes is embedded in the calculation of log-posterior probability and the revised log-posterior probability (RLPP) is regarded as the measure of mispronunciation; secondly,...
Mispronunciation detection is an important component in computer assisted language learning (CALL) system. In this work, we introduce an efficient GLDS-SVM based detection method, which is successfully used in language and speaker identification systems, and combine it with traditional methods. The main ideas include: extended MFCC features with normalized formant trajectory information, and then...
In recent years, the poly-l-proline type II (PPII) conformation has gained more and more importance. This structure plays vital roles in many biological processes. But few studies have been made to predict PPII secondary structures computationally. The support vector machine (SVM) represents a new approach to supervised pattern classification and has been successfully applied to a wide range of pattern...
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