1  A schematic overview of the Emu Speech Database Management System

1.1 Background

The core idea behind Emu today is just the same as it was when it first launched in the mid-late 1980s at CSTR, Edinburgh University and known as APS which stood for Acoustic Phonetics in S.

The core idea of Emu is:

• A speech database is a collection of utterances consisting of signal (waveform, formant, f0 etc) and annotation (label) files.
• There is a query language: annotations can be extracted from the database and read directly into R. It should be straightforward to e.g. find all tokens of [i] in the database.
• These queried lists of annotations in R can be further queried to get the corresponding signals (e.g. find the formants of the [i] tokens extracted at the previous step).

There have been some landmark changes to Emu since the APS–Edinburgh days of the 1980s.

1. In the 1990s (at Linguistics, Macquarie University, Sydney), Emu’s query language was updated to handle hierarchically structured annotations: see especially Cassidy and Harrington (2001). (The name Emu evolved out of Extended MUlti-dimensional and because we were in Australia). The query language is still in use today and is the only one of its kind in existence.

The query language is still in use today and the only one of its kind in existence.

The author of the Emu query language is Steve Cassidy who can be seen here feeding the Emu ca 1996.

The point of hierarchical annotations is to be able to query annotations at one tier with respect to another. For example the previous query could be extended to:

• Find all [i] vowels in the first syllable of trisyllabic accented words, but only if they are preceded by a function word in any L% intonational phrase.

2. From 2002–2006, the Advanced Speech Signal Processor (ASSP) toolkit developed by Michel Scheffers of the IPdS, University of Kiel was integrated into Emu (Bombien et al. 2006). ASSP then morphed into the R package wrassp ca. 2014.

3. In the last few years, the Emu engine was completely overhauled by Raphael Winkelmann with many excellent new features (see also Winkelmann, Harrington, and Jänsch 2017), e.g.:

• Emu is launched and operates entirely within the R programming environment.
• An interactive graphical user interface for analysing and visualising data: the Emu-webApp
• Extension of the query language to include regular expressions.
• Far more rapid access to extracting annotations and their signal files from the database.

1.2 The Emu-SDMS

Bombien, Lasse, Steve Cassidy, Jonathan Harrington, Tina John, and Sallyanne Palethorpe. 2006. “Recent Developments in the Emu Speech Database System.” Proceedings of the Australian Speech Science and Technology Conference. https://www.phonetik.uni-muenchen.de/~jmh/papers/emusst06.pdf.

Cassidy, Steve, and Jonathan Harrington. 2001. “Multi-Level Annotation in the Emu Speech Database Management System.” Speech Communication 33 (1–2): 61–77. https://doi.org/10.1016/S0167-6393(00)00069-8.

Winkelmann, Raphael, Jonathan Harrington, and Klaus Jänsch. 2017. “EMU-SDMS. Advanced Speech Database Management and Analysis in r.” Computer Speech & Language 45: 392–410. https://doi.org/10.1016/j.csl.2017.01.002.