@InCollection{Supelec510,
author = {Olivier Pietquin},
title = {{Machine Learning Methods for Spoken Dialogue Simulation and Optimization}},
year = {2009},
booktitle = {{Machine Learning}},
publisher = {IN-TECH},
pages = {167-184},
month = {January},
editor = {Abdelhamid Mellouk and Abdennacer Chebira},
url = {http://www.intechopen.com/source/pdfs/6063/InTech-Machine_learning_methods_for_spoken_dialogue_simulation_and_optimization.pdf},
isbn = {978-953-7619-56-1},
abstract = {Computers and electronic devices are becoming more and more
present in our day-to-day
life. This can of course be partly explained by their ability
to ease the achievement of
complex and boring tasks, the important decrease of prices or
the new entertainment styles
they offer. Yet, this real incursion in everybody’s life would
not have been possible without
an important improvement of Human-Computer Interfaces (HCI).
This is why HCI are now
widely studied and become a major trend of research among the
scientific community.
Designing “user-friendly” interfaces usually requires
multidisciplinary skills in fields such
as computer science, ergonomics, psychology, signal processing
etc. In this chapter, we
argue that machine learning methods can help in designing
efficient speech-based humancomputer
interfaces.}
}