A Review of Dialogue Systems: From Trained Monkeys to Stochastic Parrots
- URL: http://arxiv.org/abs/2111.01414v1
- Date: Tue, 2 Nov 2021 08:07:55 GMT
- Title: A Review of Dialogue Systems: From Trained Monkeys to Stochastic Parrots
- Authors: Atharv Singh Patlan, Shiven Tripathi, Shubham Korde
- Abstract summary: We aim to deploy artificial intelligence to build automated dialogue agents that can converse with humans.
We present a broad overview of methods developed to build dialogue systems over the years.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In spoken dialogue systems, we aim to deploy artificial intelligence to build
automated dialogue agents that can converse with humans. Dialogue systems are
increasingly being designed to move beyond just imitating conversation and also
improve from such interactions over time. In this survey, we present a broad
overview of methods developed to build dialogue systems over the years.
Different use cases for dialogue systems ranging from task-based systems to
open domain chatbots motivate and necessitate specific systems. Starting from
simple rule-based systems, research has progressed towards increasingly complex
architectures trained on a massive corpus of datasets, like deep learning
systems. Motivated with the intuition of resembling human dialogues, progress
has been made towards incorporating emotions into the natural language
generator, using reinforcement learning. While we see a trend of highly
marginal improvement on some metrics, we find that limited justification exists
for the metrics, and evaluation practices are not uniform. To conclude, we flag
these concerns and highlight possible research directions.
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