32 citations · 74 across the 6 of their papers we have counts for
6 papers
Identifying Discourse Markers in Spoken Dialog
Peter A. Heeman, Donna Byron, James F. Allen
In this paper, we present a method for identifying discourse marker usage in spontaneous speech based on machine learning. Discourse markers are denoted by special POS tags, and th…
Speech Repairs, Intonational Boundaries and Discourse Markers: Modeling Speakers' Utterances in Spoken Dialog
Peter A. Heeman
In this thesis, we present a statistical language model for resolving speech repairs, intonational boundaries and discourse markers. Rather than finding the best word interpretatio…
Incorporating POS Tagging into Language Modeling
Peter A. Heeman, James F. Allen
Language models for speech recognition tend to concentrate solely on recognizing the words that were spoken. In this paper, we redefine the speech recognition problem so that its g…
Intonational Boundaries, Speech Repairs and Discourse Markers: Modeling Spoken Dialog
Peter A. Heeman, James F. Allen
To understand a speaker's turn of a conversation, one needs to segment it into intonational phrases, clean up any speech repairs that might have occurred, and identify discourse ma…
Collaborating on Referring Expressions
Peter A. Heeman, Graeme Hirst
This paper presents a computational model of how conversational participants collaborate in order to make a referring action successful. The model is based on the view of language…
Detecting and Correcting Speech Repairs
Peter Heeman, James Allen
Interactive spoken dialog provides many new challenges for spoken language systems. One of the most critical is the prevalence of speech repairs. This paper presents an algorithm t…