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This paper explores several unsupervised ap- proaches to automatic keyword extraction using meeting transcripts. In the TFIDF (term frequency, inverse document frequency) weighting framework, we incorporated part- of-speech (POS) information, …...

In a meeting, it is often desirable to extract keywords from each utterance as soon as it is spoken. Thus, this paper proposes a just-in- time keyword extraction from meeting …...

We present a new hierarchical Bayesian model for unsupervised topic segmentation. This new model integrates a point-wise boundary sam- pling algorithm used in Bayesian segmenta- tion into a structured topic …...

The automated transcription of spoken lan- guage, and meetings, in particular, is be- coming more widespread as automatic speech recognition systems are becoming more accu- rate. This trend has significantly …...

AbstractAs the number of recorded meetings increases, it becomes increasingly important to utilize summarization technology to create useful summaries of these recordings. However, there is a crucial lack of annotated …...