The core idea behind Emu 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
. E.g. find all [i]
vowels in the database.
These queried lists of annotations in R
can be further queried to get the corresponding signals (*find the formants of the [i]
vowels extracted at the previous step)
There have been some landmark changes to Emu since the APS-Edinburgh days of the 1980s.
Emu
evolved out of Extended MUlti-dimensional and because we were in Australia.Here the author of the query language, Steve Cassidy which is still in use today (and the only query language of its kind) can be seen feeding the Emu ca. 1996).
The point of hierarchical annotations is to be able query annotations at one tier with respect to another. E.g., the previous query could be extended to:
[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.From 2002-2006, the ASSP signal processing toolkit developed by Michel Scheffers of the IPdS, University of Kiel was integrated into Emu Bombien et al,2006 ASSP
then morphed into library(wrassp)
ca. 2014.
In the last few years, the Emu engine was completely overhauled by Raphael Winkelmann. Many new excellent features (See also Winkelmann et al, 2017
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 signal files from very large segment lists