Publishing Partner: Cambridge University Press CUP Extra Publisher Login
amazon logo
More Info

New from Oxford University Press!


Evolutionary Syntax

By Ljiljana Progovac

This book "outlines novel and testable hypotheses, contains extensive examples from many different languages" and is "presented in accessible language, with more technical discussion in footnotes."

New from Cambridge University Press!


The Making of Vernacular Singapore English

By Zhiming Bao

This book "proposes a new theory of contact-induced grammatical restructuring" and "offers a new analytical approach to New English from a formal or structural perspective."

Academic Paper

Title: Estimating the number of segments for improving dialogue act labelling
Author: Vicent Tamarit
Institution: Universidad Politécnica de Valencia
Author: Carlos-D. Martínez-Hinarejos
Institution: Universidad Politécnica de Valencia
Author: José-Miguel Benedí
Institution: Universidad Politécnica de Valencia
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: In dialogue systems it is important to label the dialogue turns with dialogue-related meaning. Each turn is usually divided into segments and these segments are labelled with dialogue acts (DAs). A DA is a representation of the functional role of the segment. Each segment is labelled with one DA, representing its role in the ongoing discourse. The sequence of DAs given a dialogue turn is used by the dialogue manager to understand the turn. Probabilistic models that perform DA labelling can be used on segmented or unsegmented turns. The last option is more likely for a practical dialogue system, but it provides poorer results. In that case, a hypothesis for the number of segments can be provided to improve the results. We propose some methods to estimate the probability of the number of segments based on the transcription of the turn. The new labelling model includes the estimation of the probability of the number of segments in the turn. We tested this new approach with two different dialogue corpora: Switchboard and Dihana . The results show that this inclusion significantly improves the labelling accuracy.


This article appears IN Natural Language Engineering Vol. 18, Issue 1, which you can READ on Cambridge's site .

Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page