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Published in:
2011 | OriginalPaper | Chapter
An Active Learning Approach for Statistical Spoken Language Understanding
Authors : Fernando García, Lluís-F. Hurtado, Emilio Sanchis, Encarna Segarra
Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Publisher: Springer Berlin Heidelberg
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In general, large amount of segmented and labeled data is needed to estimate statistical language understanding systems. In recent years, different approaches have been proposed to reduce the segmentation and labeling effort by means of unsupervised o semi-supervised learning techniques. We propose an active learning approach to the estimation of statistical language understanding models that involves the transcription, labeling and segmentation of a small amount of data, along with the use of raw data. We use this approach to learn the understanding component of a Spoken Dialog System. Some experiments that show the appropriateness of our approach are also presented.