Parameters for Topic Boundary Detection in Multi-Party Dialogues

Abstract

We present a topic boundary detection method that searches for connections between sequences of utterances in multi party dialogues. The connections are established based on word identity. We compare our method to a state-of-the art automatic Topic boundary detection method that was also used on multi party dialogues. We checked various methods of preprocessing of the data, including stemming, lemmatization and stopword filtering with a text-based as well as speech-based stopword lists. Using standard evaluation methods we found that our method outperformed the state-of-the art method.

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