Measuring the Coherence of Dialog Responses
Applications of conversational agents are becoming widespread. However, training such agents to generate high-quality responses is still a big challenge as the quality of responses depends on various factors. One of these factors is coherence. In this thesis, we built upon one of our existing models to measure the coherence of a response to its preceding dialog utterances using BERT-based language models.