machine learning techniques in dialogue act recognition

Clicks: 279
ID: 218532
2007
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Abstract
This report addresses dialogue acts, their existing applications and techniques of automatically recognizing them, in Estonia as well as elsewhere. Three main applications are described: in dialogue systems to determine the intention of the speaker, in dialogue systems with machine translation to resolve ambiguities in the possible translation variants and in speech recognition to reduce word recognition error rate.

Several recognition techniques are described on the surface level: how they work and how they are trained. A summary of the corresponding representation methods is provided for each technique. The paper also includes examples of applying the techniques to dialogue act recognition.The author comes to the conclusion that using the current evaluation metric it is impossible to compare dialogue act recognition techniques when these are applied to different dialogue act tag sets. Dialogue acts remain an open research area, with space and need for developing new recognition techniques and methods of evaluation.

Reference Key
fiel2007eestimachine Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Mark Fišel
Journal Journal of food protection
Year 2007
DOI
10.5128/ERYa3.08
URL
http://dx.doi.org/10.5128/ERYa3.08
Keywords
Machine learning Neural network computational linguistics hidden markov model conversation analysis baltic-finnic

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