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Machine Learning Methods for Spoken Dialogue Simulation and Optimization

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.
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Submitted on : Friday, November 27, 2009 - 9:19:56 PM
Last modification on : Monday, December 14, 2020 - 2:10:02 PM


  • HAL Id : hal-00436911, version 1



Olivier Pietquin. Machine Learning Methods for Spoken Dialogue Simulation and Optimization. Abdelhamid Mellouk, Abdennacer Chebira. Machine Learning, IN-TECH, pp.167-184, 2009. ⟨hal-00436911⟩



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