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2020 AACL AACL 2020

metaCAT: A Metadata-based Task-oriented Chatbot Annotation Tool

Abstract

AbstractCreating high-quality annotated dialogue corpora is challenging. It is essential to develop practical annotation tools to support humans in this time-consuming and error-prone task. We present metaCAT, which is an open-source web-based annotation tool designed specifically for developing task-oriented dialogue data. To the best of our knowledge, metaCAT is the first annotation tool that provides comprehensive metadata annotation coverage to the domain, intent, and span information. The data annotation quality is enhanced by a real-time annotation constraint-checking mechanism. An Automatic Speech Recognition (ASR) function is implemented to allow users to paraphrase and create more diversified annotated utterances. metaCAT is publicly available for the community.

🚀 Conference Pioneer — AACL 2020
🌱 Topic Pioneer — Dialogue Systems
🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — dialogue annotation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing, Reinforcement Learning, Speech & Audio

Authors

Ximing Liu , Wei Xue , Qi Su , Weiran Nie , Wei Peng

Topics

Machine Learning > Learning Types > Weakly Supervised Learning Natural Language Processing > Generation > Dialogue Systems Natural Language Processing > Applications > Dialogue Systems

Keywords

weakly supervised learning task-oriented dialogue natural language understanding dialogue annotation metadata annotation
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