Speech Grammars for Textual Entailment Patterns in Multimodal Question Answering

Daniel Sonntag, Bogdan Sacaleanu

In: Proceedings of the Seventh Conference on International Language Resources and Evaluation. International Conference on Language Resources and Evaluation (LREC-10) May 19-21 Valletta Malta ISBN 2-9517408-6-7 European Language Resources Association (ELRA) 2010.


Over the last several years, speech-based question answering (QA) has become very popular in contrast to pure search engine based approaches on a desktop. Open-domain QA systems are now much more powerful and precise, and they can be used in speech applications. Speech-based question answering systems often rely on predefined grammars for speech understanding. In order to improve the coverage of such complex AI systems, we reused speech patterns used to generate textual entailment patterns. These can make multimodal question understanding more robust. We exemplify this in the context of a domain-specific dialogue scenario. As a result, written text input components (e.g., in a textual input field) can deal with more flexible input according to the derived textual entailment patterns. A multimodal QA dialogue spanning over several domains of interest, i.e., personal address book entries, questions about the music domain and politicians and other celebrities, demonstrates how the textual input mode can be used in a multimodal dialogue shell.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence