Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge

Authors Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, Salvador Abreu

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Author Details

Dietmar Seipel
  • Department of Computer Science, Universität Würzburg, Germany
Benjamin Förster
  • Department of Computer Science, Universität Würzburg, Germany
Magnus Liebl
  • Department of Computer Science, Universität Würzburg, Germany
Marcel Waleska
  • Department of Computer Science, Universität Würzburg, Germany
Salvador Abreu
  • Nova-Lincs, University of Évora, Portugal

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Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, and Salvador Abreu. Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 6:1-6:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


We are extending the keyword-based query interface DdQl for relational databases which is based on contextual background knowledge such as suitable join conditions and which was proposed in [{Dietmar Seipel, 2021]. In the previous paper, join conditions were extracted from existing referential integrity (foreign key) constraints of the database schema, or they could be learned from other, previous database queries. In this paper, we describe a speech-to-text component for entering the query keywords based on the system Whisper. Keywords, which have been recognized wrongly by Whisper can be corrected to similarly sounding words. Again, the context of the database schema can help here. For users with a limited knowledge of the schema and the contents of the database, the approach of DdQl can help to provide useful suggestions for query implementations in Sql or Datalog, from which the user can choose one. Our tool DdQl can be run in a docker image; it yields the possible queries in Sql and a special domain specific rule language that extends Datalog. The Datalog variant allows for additional user-defined aggregation functions which are not possible in Sql.

Subject Classification

ACM Subject Classification
  • Information systems → Relational database query languages
  • Information systems → Relational database model
  • Knowledge Bases
  • Natural Language Interface
  • Logic Programming
  • Definite Clause Grammars
  • Referential Integrity Constraints
  • Speech-to-Text


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