Querying Databases of Annotated Speech

TL;DR

This paper discusses modeling and querying annotated speech databases, addressing their complex, multidimensional, and temporal nature, and introduces query languages and tools for linguistic data management.

Contribution

It harmonizes two modeling approaches for annotated speech databases and presents query languages and applications for linguistic data analysis.

Findings

Development of harmonized models for speech databases

Description of query languages for complex data retrieval

Implementation of open-source tools for linguistic database management

Abstract

Annotated speech corpora are databases consisting of signal data along with time-aligned symbolic `transcriptions'. Such databases are typically multidimensional, heterogeneous and dynamic. These properties present a number of tough challenges for representation and query. The temporal nature of the data adds an additional layer of complexity. This paper presents and harmonises two independent efforts to model annotated speech databases, one at Macquarie University and one at the University of Pennsylvania. Various query languages are described, along with illustrative applications to a variety of analytical problems. The research reported here forms a part of several ongoing projects to develop platform-independent open-source tools for creating, browsing, searching, querying and transforming linguistic databases, and to disseminate large linguistic databases over the internet.