SpeakQL: Towards Speech-driven Multi-modal Querying

Abstract

Natural language and touch-based interfaces are making data querying significantly easier. But typed SQL remains the gold standard for query sophistication although it is painful in many querying environments. Recent advancements in automatic speech recognition raise the tantalizing possibility of bridging this gap by enabling spoken SQL queries. In this work, we outline our vision of one such new query interface and system for regular SQL that is primarily speech-driven. We propose an end-to-end architecture for making spoken SQL querying effective and efficient and present initial empirical results to understand the feasibility of such an approach. We identify several open research questions and propose alternative solutions that we plan to explore.