Bootstrapping Conversational Agents With Weak Supervision

By Neil Rohit Mallinar, Abhishek Shah, Rajendra Ugrani, Ayush Gupta, Manikandan Gurusankar, Tin Kam Ho, Q. Liao, Yunfeng Zhang, R. Bellamy, Robert Yates and 3 more. 2018

21 citations recorded by the source corpus.

Many conversational agents in the market today follow a standard bot development framework which requires training intent classifiers to recognize user input. The need to create a proper set of training examples is often the bottleneck in the development process. In many occasions agent developers have access to historical chat logs that can provide a good quantity as well as coverage of training examples. However, the cost of labeling them with tens to hundreds of intents often prohibits taking full advantage of these chat logs. In this paper, we present a framework called search, label, and propagate (SLP) for bootstrapping intents from existing chat logs using weak supervision. The framework reduces hours to days of labeling effort down to minutes of work by using a search engine to find examples, then relies on a data programming approach to automatically expand the labels. We report on a user study that shows positive user feedback for this new approach to build conversational agents, and demonstrates the effectiveness of using data programming for autolabeling. While the system is developed for training conversational agents, the framework has broader application in significantly reducing labeling effort for training text classifiers.

Subfields: Artificial Intelligence, Computer Science Applications, Management of Technology and Innovation, Natural Language Processing, Reinforcement Learning

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In Artificial Intelligence

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Braden Hancock

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In Reinforcement Learning

Citations in the corpus

Learning from Dialogue after Deployment: Feed Yourself, Chatbot! (2019, positive): “Other applications of weak supervision to dialogue (Mallinar et al., 2019) and relation extraction have observed similar results (Bunescu and Mooney, 2007; Hancock et al.”