Advanced ELAN
1
Info
1.1
Course goals
1.2
Course structure
1.3
Schedule
1.4
Resources
1.5
Practical info
2
Introduction
2.1
Elan and Praat – strengths and weaknesses
2.2
Linguistic software
2.3
ELAN corpora
2.4
Preprocessing
2.4.1
Example of preprocessing workflow
2.5
Analysis workflows
2.6
When to write back to ELAN file
2.7
Annotations as an independent dataset
3
Tools
3.1
Git
3.2
R
3.2.1
tidytext
3.2.2
xml2
3.3
Python
3.3.1
pympi
3.4
Anaconda
3.5
reticulate
3.6
PraatScript
3.7
XPath
3.7.1
Examples
4
ELAN file structure
4.1
Minimal file
4.1.1
Participant name convention
4.2
Tier type naming convention
4.3
Hierarchies
4.4
Discussion
5
Parsing ELAN files to R
5.0.1
Questions
5.0.2
Example
5.1
Customizing to tier pattern
5.2
Why to read ELAN files into R?
5.3
Parsing with FRelan package
6
Exploring and manipulation
6.1
Basic exploration with R
6.1.1
filter()
6.1.2
slice()
6.1.3
count(), add_count()
6.1.4
mutate
6.1.5
rename
6.1.6
lag(), lead()
6.1.7
str_extract()
6.1.8
str_detect()
6.1.9
if_else()
6.2
Manipulating ELAN files with Pympi
7
Pympi examples
7.1
Creating a new ELAN file
7.2
Populating the ELAN file with content
7.3
Merging ELAN files
8
Shiny components
8.1
DT
8.2
Leaflet
8.3
ggplot2
8.4
Advantages and disadvantages of Shiny
9
Example: Interaction with emuR
9.1
Procedure
10
Example: Interaction with Praat
10.1
Research questions
10.2
Implementation
10.3
Shiny application
10.4
Observations
10.5
Exercise
11
Example: Concordances and map
11.1
Use
12
Example: Preprocessing workflow
12.1
From points to polygon
13
Final Words
References
Draft version, not to be cited without permission.
Advanced ELAN manipulation and analysis
Section 7
Pympi examples
7.1
Creating a new ELAN file
7.2
Populating the ELAN file with content
7.3
Merging ELAN files