Summary Grounded Conversation Generation

• URL: http://arxiv.org/abs/2106.03337v1
• Date: Mon, 7 Jun 2021 04:46:31 GMT
• Title: Summary Grounded Conversation Generation
• Authors: Chulaka Gunasekara, Guy Feigenblat, Benjamin Sznajder, Sachindra Joshi, David Konopnicki
• Abstract summary: We show how pre-trained language models can be used to generate entire conversations, given only a summary of a conversation as the input. We also show that the accuracy of conversation summarization can be improved by augmenting a conversation summarization dataset with generated conversations.
• Score: 10.470157142861174
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Many conversation datasets have been constructed in the recent years using crowdsourcing. However, the data collection process can be time consuming and presents many challenges to ensure data quality. Since language generation has improved immensely in recent years with the advancement of pre-trained language models, we investigate how such models can be utilized to generate entire conversations, given only a summary of a conversation as the input. We explore three approaches to generate summary grounded conversations, and evaluate the generated conversations using automatic measures and human judgements. We also show that the accuracy of conversation summarization can be improved by augmenting a conversation summarization dataset with generated conversations.

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