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Recently, significant progress has been witnessed in automatic language identification. Perhaps the most important development is the application of discriminative training. However, efficient and effective discriminative training for language pair identification is still a challenging problem. Specifically, with the increase of the number of languages to be recognized, the number of the language...
Finding the effective image representation is an important problem for classification. Previous approaches have demonstrated the utility of the bag-of-feature (BoF) models. These methods are interesting due to the computational efficiency and conceptual simplicity. However, it is achieved by discarding the spatial context information. Furthermore, it may suffer from the quantization error introduced...
Because of diversity of hardware environments, building scalable text-to-speech system is an important issue of Corpus-based text-to-speech system. This paper proposes and analyses three semantic computing problems of building scalable text to speech system: similarity calculation, granular computing and automated instances-pruning process framework. According to these, an acoustic clustering algorithm-NuClustering-VPA...
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