Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data

In this demonstration, we present SpeakQL, a speech-driven query system and interface for structured data. SpeakQL supports a tractable and practically useful subset of regular SQL, allowing users to query in any domain with unbounded vocabulary with the help of speech/touch based user-in-the-loop mechanisms for correction. When querying in such domains, automatic speech recognition introduces countless forms of errors in transcriptions, presenting us with a technical challenge. We characterize such errors and leverage our observations along with SQL's unambiguous context-free grammar to first correct the query structure. We then exploit phonetic representation of the queried database to identify the correct Literals, hence delivering the corrected transcribed query. In this demo, we show that SpeakQL helps users reduce time and effort in specifying SQL queries significantly. In addition, we show that SpeakQL, unlike Natural Language Interfaces and conversational assistants, allows users to query over any arbitrary database schema. We allow the audience to explore SpeakQL using an easy-to-use web-based interface to compose SQL queries.

[1]  Fei Li,et al.  Constructing an Interactive Natural Language Interface for Relational Databases , 2014, Proc. VLDB Endow..

[2]  Vraj Shah,et al.  SpeakQL: Towards Speech-driven Multimodal Querying , 2019, SIGMOD '19.

[3]  Carsten Binnig,et al.  Making the Case for Query-by-Voice with EchoQuery , 2016, SIGMOD Conference.

[4]  Arun Kumar,et al.  SpeakQL: Towards Speech-driven Multi-modal Querying , 2017, HILDA@SIGMOD.

[5]  Carsten Binnig,et al.  Vizdom: Interactive Analytics through Pen and Touch , 2015, Proc. VLDB Endow..

[6]  编程语言 Query by Example , 2010, Encyclopedia of Database Systems.