Data-Driven Dialogue Systems: Models, Algorithms, Evaluation, and Ethical Challenges
Author(s)
Pineau, Joelle
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Abstract
The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent
paradigm. A growing number of dialogue systems use conversation strategies that are learned from
large datasets. In this talk I will review several recent models and algorithms based on both
discriminative and generative models, and discuss new results on the proper performance measures
for such systems. Finally, I will highlight potential ethical issues that arise in dialogue systems
research, including: implicit biases, adversarial examples, privacy violations, and safety concerns.
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Date
2018-02-22
Extent
70:57 minutes
Resource Type
Moving Image
Text
Text
Resource Subtype
Lecture
Flyer
Flyer