TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition

Abstract

TEXTOIR is the first integrated and visualized platform for text open intent recognition. It is composed of two main modules: open intent detection and open intent discovery. Each module integrates most of the state-of-the-art algorithms and benchmark intent datasets. It also contains an overall framework connecting the two modules in a pipeline scheme. In addition, this platform has visualized tools for data and model management, training, evaluation and analysis of the performance from different aspects. TEXTOIR provides useful toolkits and convenient visualized interfaces for each sub-module (Toolkit code: https://github.com/thuiar/TEXTOIR), and designs a framework to implement a complete process to both identify known intents and discover open intents (Demo code: https://github.com/thuiar/TEXTOIR-DEMO).

Published in ACL 2021, demo paper

References in corpus (1)

• Deep Open Intent Classification with Adaptive Decision Boundary

Cited by in corpus (4)

• MIntRec: A New Dataset for Multimodal Intent Recognition
• Learning Discriminative Representations and Decision Boundaries for Open Intent Detection
• A Clustering Framework for Unsupervised and Semi-supervised New Intent Discovery
• Duplex Conversation: Towards Human-like Interaction in Spoken Dialogue Systems