Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation

In this paper, we tackle the challenge of inadequate and costly training data that has hindered the development of conversational question answering (ConvQA) systems. Enterprises have a large corpus of diverse internal documents. Instead of relying on a searching engine, a more compelling approach for people to comprehend these documents is to create a dialogue system. In this paper, we propose a robust dialog synthesising method called SynCARS. We learn the segmentation of data for the dialog task instead of using segmenting at sentence boundaries. The synthetic dataset generated by our proposed method achieves superior quality when compared to WikiDialog, as assessed through machine and human evaluations. By employing our inpainted data for ConvQA retrieval system pre-training, we observed a notable improvement in performance across standard benchmark datasets. 1 1 Our model and dataset are publicly available at https: //github.com/wufanyou/SynCARS . WD: When did the Czechs settle in Argentina? WD: What led to the split? A: It is estimated that around 40,000 Czechs arrived to Argentina until 1970.