Paper: Experiments On Unsupervised Learning For Extracting Relevant Fragments From Spoken Dialog Corpus

ACL ID W00-0715
Title Experiments On Unsupervised Learning For Extracting Relevant Fragments From Spoken Dialog Corpus
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000
Authors

In this paper are described experiments on un- supervised learning of the domain lexicon and relevant phrase fragments from a dialog cor- pus. Suggested approach is based on using do- main independent words for chunking and us- ing semantical predictional power of such words for clustering and automatic extraction phrase fragments relevant to dialog topics.