Koshiro Okano


Contrastive Response Pairs for Automatic Evaluation of Non-task-oriented Neural Conversational Models
Koshiro Okano | Yu Suzuki | Masaya Kawamura | Tsuneo Kato | Akihiro Tamura | Jianming Wu
Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue

Responses generated by neural conversational models (NCMs) for non-task-oriented systems are difficult to evaluate. We propose contrastive response pairs (CRPs) for automatically evaluating responses from non-task-oriented NCMs. We conducted an error analysis on responses generated by an encoder-decoder recurrent neural network (RNN) type NCM and created three types of CRPs corresponding to the three most frequent errors found in the analysis. Three NCMs of different response quality were objectively evaluated with the CRPs and compared to a subjective assessment. The correctness obtained by the three types of CRPs were consistent with the results of the subjective assessment.