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arxiv:1910.11790
Measuring Conversational Fluidity in Automated Dialogue Agents
Published on Oct 25, 2019
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Abstract
An automated classifier trained on human ratings improves measurement of dialogue fluidity over existing metrics.
Generated by thinkingmachines/Inkling-Small
We present an automated evaluation method to measure fluidity in conversational dialogue systems. The method combines various state of the art Natural Language tools into a classifier, and human ratings on these dialogues to train an automated judgment model. Our experiments show that the results are an improvement on existing metrics for measuring fluidity.
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