Events & News
MS Thesis Defense
| Category | Lecture |
| Date | Friday, May 9, 2014 |
| Time | 1:30 pm |
| Concludes | 2:30 pm |
| Location | Gould-Simpson 701 |
| Details | Review Committee: Paul Cohen, Clayton Morrison & John Hartman |
| Speaker | Enrique Noriega Atala |
| Title | Master of Science Candidate |
| Affiliation | Computer Science, University of Arizona |
An Evaluation Framework for Adaptive Rational User Interfaces
With the rise of powerful mobile devices and the broad availability of computing power, Automatic Speech Recognition is becoming ubiquitous. Despite the rapid advance and active research in the field, a flawless ASR system is still far from existence. Because of this, interactive applications that make use of ASR technology not always behave smoothly and when not, the user must be engaged to repair the mistakes in the transcriptions.
When the user is engaged, he can repair these errors with different strategies. These strategies work better under different contexts. In this thesis, we explore a rational user interface that makes use of machine learning models to make its best effort in presenting the best repair strategy available to keep the interaction between the user and the system as smooth as possible. A study is conducted to determine how different candidate policies perform and conclusions are drawn from the analysis of the collected results.
Once the analysis is performed, the methodology that was used is generalized in terms of a decision theoretical framework that can be used to evaluate the performance of the other rational user interfaces that try to optimize an expected cost or utility.
After the generalization, the framework is placed in the context of the relevant literature and some potential future work is outlined.