Question-Answering Dialog System for Large Audiovisual Archives

摘要

In this paper, we present our spoken dialog system that serves as a search interface of the MALACII archive. The voice interface and natural language input allow the users to retrieve information contained in large audiovisual archives more comfortably. Especially, finding answers to a more structured question should be easier in comparison with typical search input options. The dialog is build on top of a system that automatically annotates and indexes the archive using automatic speech recognition. These indexes were searchable so far only in a full-text search for any arbitrary text query Our proposed approach improves this system and leverages named entity recognition to create a knowledge base of semantic information contained in the recognized utterances. We describe the design of the dialog system, as well as the automatic knowledge base generation and the approach to creating queries using a spoken natural language as an input.