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Emotion recognition from speech plays an important role in developing affective and intelligent systems. This study investigates sentence-level emotion recognition. We propose to use a two-step approach to leverage information from subsentence segments for sentence level decision. First we use a segment level emotion classifier to generate predictions for segments within a sentence. A second component...
The multi-modal corpus is established on the "theory of speechrdquo. In this paper, a framework of multi-modal corpus for mandarin learning system is presented. The system included five layers which are the physical storage layer, the data description layer, the network layer, the filter layer and the user layer. This system framework is based on the J2EE technologies. The principles of data...
In this paper, we present a hidden Markov model (HMM) approach to segment meeting transcripts into topics. To learn the model, we use unsupervised learning to cluster the text segments obtained from topic boundary information. Using modified WinDiff and Pk metrics, we demonstrate that an HMM outperforms LCSeg, a state-of-the-art lexical chain based method for topic segmentation using the ICSI meeting...
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