Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots

Understand

In this paper, we study the problem of employing pre-trained language models for multi-turn response selection in retrieval-based chatbots.

• A new model, named Speaker-Aware BERT (SA-BERT), is proposed in order to make the model aware of the speaker change information, which is an important and intrinsic property of multi-turn dialogues.
• Furthermore, a speaker-aware disentanglement strategy is proposed to tackle the entangled dialogues.
• This strategy selects a small number of most important utterances as the filtered context according to the speakers' information in them.