Voice-based Data Exploration : Chatting with your Database

Recent advances in automatic speech recognition and natural language processing have led to a new generation of robust voice-based interfaces. Yet, there is very little work on using voice-based interfaces to query database systems. In fact, one might even wonder who in her right mind would want to query a database system using voice commands! With this paper, we make the case for querying database systems using a voice-based interface, a new querying and interaction paradigm we call Query-by-Voice (QbV ). We will show the practicality and utility of QbV for relational DBMSs using a using a proof-ofconcept system called EchoQuery. There exists already work for building natural language interfaces for databases. A first major difference to this line of work is, that we use recent deep-learning models to allow for a robust translation from natural language to SQL. Another major difference from existing work is that the query interface of EchoQuery is inspired by regular human-to-human conversations in order to be natural for the user. ACM Reference Format: Prasetya Utama, Nathaniel Weir, Carsten Binnig, and Ugur Çetintemel. 2017. Voice-based Data Exploration: Chatting with your Database. In Proceedings of SCAI’17 . ACM, New York, NY, USA, 6 pages.