2019
INTERSPEECH
INTERSPEECH 2019
Multimodal Dialog with the MALACH Audiovisual Archive
Abstract
In this paper, we present a multimodal dialog system capable of information retrieval from the large audiovisual archive MALACH of Holocaust testimonies. The users can use spoken natural language queries to search the archive. A graphical user interface allows the users to quickly view footage with the answers and explore their context. The dialog was deployed in two languages — English and Czech. The system uses automatic speech recognition and natural language processing for knowledge base construction and for processing of the user’s input.
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Interdisciplinary Bridge
— Natural Language Processing and Speech & Audio
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Trend Setter
— Information Retrieval
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Keyword Pioneer
— natural language query
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Hot Topic Early Bird
— information retrieval
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio