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Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
Today, most dialogue systems are fully or partly built using neural network architectures. A crucial prerequisite for the creation of a goaloriented neural network dialogue system is a dataset that represents typical dialogue scenarios and includes various semantic annotations, e.g. intents, slots and dialogue actions, that are necessary for training a particular neural network architecture. In this demonstration paper, we present an easy to use interface and its backend which is oriented todoi:10.18653/v1/2021.eacl-demos.35 fatcat:jkodejqjbbecfepabpo4b7b4ja