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Active learning can be used for the maintenance of a deployed spoken dialog system (SDS) that evolves with time and when large collection of dialog traces can be collected on a daily basis. At the spoken language understanding (SLU) level this maintenance process is crucial as a deployed SDS evolves quickly when services are added, modified or dropped. Knowledge-based approaches, based on manually...
In this paper, we study how to generate in-domain data for statistical language model adaptation in a Chinese voice search dialogue system. Given limited amount of in-domain data, we use unsupervised clustering to induce semantic classes and structures from the first part of test data. These structures are further augmented with domain information to generate large amount of in-domain data. Lastly...
In this paper, we investigate the problem of mispronunciation detection by considering the influence of speaker and syllables. Machine learning techniques are used to make our method more convenient and flexible for new features, such as syllables normalization. The experimental results on our database, consisting of 9898 syllables pronounced by 100 speakers, show the effectiveness of our method by...
The problem of content-based image and video retrieval with textual queries is often posed as that of visual concept classification, where classifiers for a set of predetermined visual concepts are trained using a set of manually annotated images. Such a formulation implicitly assumes that the training data has similar distributional characteristics as that of the data which need to be indexed. In...
We examine in detail some properties of gesture recognition models which utilize a reduced number of parameters and lower algorithmic complexity compared to traditional hidden Markov models. We show that the reduced parameter models are comparable to standard HMM-based gesture recognition models in their ability to effectively model gestures, and in some cases superior when training data is limited...
A real-time highlight extraction system using the caption information has been proposed to detect and classify the highlight events of the baseball games. The system contains several stages: caption extraction, caption identification, content recognition, and model-indexing decision stages. A superimposed caption in the baseball videos is extracted using a multi-frame averaging technique. After extracting...
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