G2P Frysk

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G2P Frysk is a web app for converting Frisian text to phonetic IPA transcriptions. Comments are welcome and can be sent to .

The following people were involved in the development of UDPipe Frysk: Hans Van de Velde (Fryske Akademy, project manager), Wilbert Heeringa (Fryske Akademy, implementation G2P Frysk), Eduard Drenth (building web service), Pieter Duijff (Fryske Akademy, advice), Jelske Dijkstra (Fryske Akademy, advice), Hindrik Sijens (Fryske Akademy, advice).

Web service

A web service has been developed by Eduard Drenth.

If you want to process a text file 'Frysk.txt' and save the output as a TSV file, give the command:

curl --data-binary '@Frysk.txt' -H 'Content-Type: text/plain' https://frisian.eu/graph2phonservice/rest/graph2phon/process

If you want to process the text 'Praat mar Frysk' and save the output as TSV file, give the command:

curl --data-binary 'Praat mar Frysk' -H 'Content-Type: text/plain' https://frisian.eu/graph2phonservice/rest/graph2phon/process

For bigger texts use the command line script .

System requirements

G2P Frysk runs best on a computer with a monitor with a minimum resolution of 1370 x 870 (width x height). The use of Chrome, Chromium, Firefox or Opera as a web browser is to be preferred.

How to cite this program

Hans Van de Velde, Wilbert Heeringa, Eduard Drenth, Pieter Duijff, Jelske Dijkstra, Hindrik Sijens 2021, G2P Frysk, Fryske Akademy / University of Groningen, Campus Fryslân, viewed date, <https://frisian.eu/graph2phonapp/>.


G2P Frysk is based on (the Python wrapper for) the Phonetisaurus grapheme to phoneme tool. With Phonetisaurus a g2p corpus was trained on the basis of the Frysk Hânwurdboek, the Foarkarswurdlist and a short supplementary list. In the app itself this g2p corpus is used by Phonetisaurus in order to convert orthographic transcriptions into phonetic IPA transcriptions. The interface of G2P Frysk is implemented as a Shiny app. Shiny was developed by RStudio. This app uses the following R packages:

  • base

    R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

  • shiny

    Winston Chang, Joe Cheng, J.J. Allaire, Yihui Xie and Jonathan McPherson (2017). shiny: Web Application Framework for R. R package version 1.0.0. https://CRAN.R-project.org/package=shiny

  • shinyjs

    Dean Attali (2018). shinyjs: Easily Improve the User Experience of Your Shiny Apps in Seconds. R package version 1.0. https://CRAN.R-project.org/package=shinyjs

  • shinyWidgets

    Victor Perrier, Fanny Meyer and David Granjon (2019). shinyWidgets: Custom Inputs Widgets for Shiny. R package version 0.5.0. https://CRAN.R-project.org/package=shinyWidgets

  • shinysky

    Dai ZJ (2019). shinysky: A Set of Shiny Components and Widgets. R package version 0.1.3. https://github.com/AnalytixWare/ShinySky

  • readr

    Hadley Wickham, Jim Hester and Romain Francois (2018). readr: Read Rectangular Text Data. R package version 1.3.1. https://CRAN.R-project.org/package=readr

  • readtext

    Kenneth Benoit and Adam Obeng (2019). readtext: Import and Handling for Plain and Formatted Text Files. R package version 0.75. https://CRAN.R-project.org/package=readtext

  • textreadr

    Rinker, T. W. (2018). textreadr: Read Text Documents into R version 0.9.0. Buffalo, New York. http://github.com/trinker/textreadr

  • openxlsx

    Philipp Schauberger and Alexander Walker (2020). openxlsx: Read, Write and Edit xlsx Files. R package version 4.2.3. https://CRAN.R-project.org/package=openxlsx

  • stringr

    Hadley Wickham (2019). stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.4.0. https://CRAN.R-project.org/package=stringr

  • tokenizers

    Lincoln A. Mullen et al., "Fast, Consistent Tokenization of Natural Language Text," Journal of Open Source Software 3, no. 23 (2018): 655, https://doi.org/10.21105/joss.00655.

  • ipa

    Alexander Rossell Hayes (2020). ipa: convert between phonetic alphabets. R package version 0.1.0. https://github.com/rossellhayes/ipa

  • ggplot2

    H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.


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This app is provided 'as is' without warranty of any kind, either express or implied, including, but not limited to, the implied warranties of fitness for a purpose, or the warranty of non-infringement. Without limiting the foregoing, the Fryske Akademy makes no warranty that: 1) the app will meet your requirements, 2) the app will be uninterrupted, timely, secure or error-free, 3) the results that may be obtained from the use of the app will be effective, accurate or reliable, 4) the quality of the app will meet your expectations, 5) any errors in the app will be corrected.

The app and its documentation could include technical or other mistakes, inaccuracies or typographical errors. The Fryske Akademy may make changes to the app or documentation made available on its web site. The app and its documentation may be out of date, and the Fryske Akademy makes no commitment to update such materials.

The Fryske Akademy assumes no responsibility for errors or ommissions in the app or documentation available from its web site.

In no event shall the Fryske Akademy be liable to you or any third parties for any special, punitive, incidental, indirect or consequential damages of any kind, or any damages whatsoever, including, without limitation, those resulting from loss of use, data or profits, whether or not the Fryske Akademy has been advised of the possibility of such damages, and on any theory of liability, arising out of or in connection with the use of this software.

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