Part-of-speech histograms for genre classification of text

Authors:
S. Feldman;M. A. Marin;M. Ostendorf;M. R. Gupta
Affiliations:
Dept. of Electrical Engineering, University of Washington, Seattle, 98195, USA;Dept. of Electrical Engineering, University of Washington, Seattle, 98195, USA;Dept. of Electrical Engineering, University of Washington, Seattle, 98195, USA;Dept. of Electrical Engineering, University of Washington, Seattle, 98195, USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Abstract

This work addresses the problem of classifying the genre of text, which is useful for a variety of language processing problems. We propose statistics of POS histograms as classification features, coupled with a quadratic discriminant classifier. In experiments on six different text and speech genres, we demonstrate enhanced performance compared to standard techniques using word frequency count features and POS trigram features. Experiments on genres that were not seen in training show intuitive overlaps with the training classes.