Latent semantic analysis for dialogue act classification

Abstract

This paper presents our experiments in applying Latent Semantic Analysis (LSA) to dialogue act classification. We employ both LSA proper and LSA augmented in two ways. We report results on DIAG, our own corpus of tutoring dialogues, and on the CallHome Spanish corpus. Our work has the theoretical goal of assessing whether LSA, an approach based only on raw text, can be improved by using additional features of the text.