EMU-SDMS: Advanced speech database management and analysis in R. (September 2017) - Winkelmann, Raphael; Harrington, Jonathan; Jänsch, Klaus
Highlights: The EMU-SDMS introduces a new set of speech database management and analysis tools that have been designed to work entirely in R. The EMU-SDMS introduces a web based annotation tool for hierarchical and non-hierarchical annotation structures that can also be used for collaborative labeling efforts. The EMU-SDMS introduces a package to perform common speech signal processing routines (e.g. formant calculation) in R. The EMU-SDMS provides powerful general purpose annotation structure modeling capabilities that surpass those of many other systems. The EMU-SDMS provides efficient query mechanics for complex hierarchical annotation structures. Abstract: The amount and complexity of the often very specialized tools necessary for working with spoken language databases has continually evolved and grown over the years. The speech and spoken language research community is expected to be well versed in multiple software tools and have the ability to switch seamlessly between the various tools, sometimes even having to script ad-hoc solutions to solve interoperability issues. In this paper, we present a set of tools that strive to provide an all-in-one solution for generating, manipulating, querying, analyzing and managing speech databases. The tools presented here are centered around the R language and environment for statistical computing and graphics (R Core Team, 2016), which benefits users by significantly reducing the number of tools the researchers have to familiarize themselves with. This paper introduces the next iteration of the EMU system that, although based on the core concepts of the legacy system, is a newly designed and almost entirely rewritten set of modern spoken language database management tools.