emuR - Main Package of the EMU Speech Database Management System
The emuR package provides the next iteration of the EMU Speech Database Management System with database management, data extraction, data preparation and data visualization facilities.
This package is part of the next iteration of the EMU Speech Database Management System (EMU-SDMS) which aims to be as close to an all-in-one solution for generating, manipulating, querying, analyzing and managing speech databases as possible. For an overview of the system please visit this URL: http://ips-lmu.github.io/EMU.html.
It can be viewed as the main component of the EMU-SDMS as it acts as the central instance that is able to interact with every component of the system. It takes care of database managing duties by being able to interact with a speech database that is stored in the emuDB format. Further, it has easy to understand and learn yet expressive and powerful querying mechanics, that allow the user to easily query the annotation structures of the database. Lastly it provides easy data extraction capabilities that extract data (e.g. formant values) which corresponds to the result of a query.
For an introduction to the emuR package please see the emuR_intro
vignette
by calling: vignette('emuR_intro')
For information about the emuDB
database format please see the emuDB
vignette by calling: vignette('emuDB')
For information about the query language used by the EMU-SDMS please see the EQL
vignette by calling: vignette('EQL')
Typical work-flow in emuR (emuDB required):
Load database into current R session - load_emuDB
Database annotation / visual inspection -
serve
and connect the EMU-webApp to the local server
Query database - query
(sometimes
followed by requery_hier
or requery_seq
)
Get trackdata (e.g. formant values) for the result
of a query - get_trackdata
Data preparation
Visual data inspection
Further analysis and statistical processing
TIP: for a browsable overview of all the functions provided by emuR simply
run the command help.start()
-> click on packages -> click on emuR
Harrington, J. (2010). The Phonetic Analysis of Speech Corpora. Blackwell.
## Not run: # create demo data including an emuDB called "ae" create_emuRdemoData(dir = tempdir()) # construct path to demo emuDB path2ae = file.path(tempdir(), "emuR_demoData", "ae") # load emuDB into current R session ae = load_emuDB(path2ae) # query loaded emuDB lvowels = query(ae, "Phonetic = i: | u: | o:") # extract labels from query result lvowels.labs = label(lvowels) # list all ssffTrackDefinitions of emuDB list_ssffTrackDefinitions(ae) # get formant trackdata defined in ssffTrackDefinitions "fm" for query result lvowels.fm = get_trackdata(ae, lvowels, "fm") # extract track values at temporal midpoint of segments lvowels.fmCut = dcut(lvowels.fm, .5, prop = TRUE) # Plot the data as time signal and formant card dplot(lvowels.fm[,1:2], lvowels.labs, normalise=TRUE, main = "Formants over vowel duration") eplot(lvowels.fmCut[,1:2], lvowels.labs, dopoints=TRUE, doellipse=FALSE, main = "F1/F2 of vowel midpoint", form=TRUE, xlab = "F2 in Hz", ylab = "F1 in Hz") # Plot of spectral data from 50% of aspiration duration hs = query(ae,"Phonetic = H") hs.labs = label(hs) hs.dft = get_trackdata(ae, hs, "dft") hs.dftCut = dcut(hs.dft, .5, prop=TRUE) plot(hs.dftCut, hs.labs, main = "Spectral data of aspiration") ## End(Not run)
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