Towards Automatic Identification of Discourse Markers in Dialogs: the Case of 'Like'

Zufferey, Sandrine; Popescu-Belis, Andrei (2004). Towards Automatic Identification of Discourse Markers in Dialogs: the Case of 'Like'. In: Proceedings of SIGDIAL'04 (5th SIGdial Workshop on Discourse and Dialogue). Cambridge, Massachussets. 30.04.-01.05.2004.

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This article discusses the detection of discourse
markers (DM) in dialog transcriptions,
by human annotators and by automated
means. After a theoretical discussion of the
definition of DMs and their relevance to natural
language processing, we focus on the role
of like as a DM. Results from experiments
with human annotators show that detection of
DMs is a difficult but reliable task, which requires
prosodic information from soundtracks.
Then, several types of features are defined for
automatic disambiguation of like: collocations,
part-of-speech tags and duration-based
features. Decision-tree learning shows that for
like, nearly 70% precision can be reached,
with near 100% recall, mainly using collocation
filters. Similar results hold for well, with
about 91% precision at 100% recall.

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