Below I briefly introduce two tools that I have found particularly useful for my research, Jupyter and R Shiny.
Jupyter notebooks
is a loose acronym for “Julia, Python and R”. Jupyter notebooks allow users to create documents that contain code, equations, visualizations and explanatory text. The code is live when running that notebook. Notebooks can be exported in different formats, including HTML, R Markdown, and PDF. I find Jupyter notebooks extremely useful for collaboration and public code sharing.
Here are two examples of HTML output of Jupyter notebooks I created:
[]
[]
R Shiny
is an R package that allows users to build interactive web applications. Shiny applications can be extended with CSS themes, htmlwidgets, and javascript actions in a straightforward manner. This allows for the creation of rich user interfaces. Here are two examples of Shiny applications I created.
[]
[]
Jupyter notebooks
is a loose acronym for “Julia, Python and R”. Jupyter notebooks allow users to create documents that contain code, equations, visualizations and explanatory text. The code is live when running that notebook. Notebooks can be exported in different formats, including HTML, R Markdown, and PDF. I find Jupyter notebooks extremely useful for collaboration and public code sharing.
Here are two examples of HTML output of Jupyter notebooks I created:
[]
GAMM analysis of ERP data
A brief example of an analysis of ERP data using generalized-additive mixed-effect models (GAMMs).
[]
Horse race puzzle
“You have 25 horses, and 5 race tracks. You do not have a watch. How many races do you need to find the 5 fastest horses?” (extremely elegant former Google interview question).
R Shiny
is an R package that allows users to build interactive web applications. Shiny applications can be extended with CSS themes, htmlwidgets, and javascript actions in a straightforward manner. This allows for the creation of rich user interfaces. Here are two examples of Shiny applications I created.
[]
Auditory data inspection (refresh if necessary)
I developed this application for the class “Reduction in spontaneous speech”. The application allows
for the inspection of acoustic data from an auditory corpus of Mandarin Chinese, the TWMandarin corpus. For each pronunciation, waveforms with
aligned transcriptions and audio files are provided. The acoustic signal can be inspected in detail by zooming into specific parts of the
speech signal.
[]
Vowel space (refresh if necessary)
I developed this application for the class “Phonetics and phonology of Mandarin Chinese”. The
application visualizes the vowel space of a male speaker of Mandarin Chinese for 1,000 pronunciation of one and two character words
in Mandarin Chinese. Detailed information about pronunciations is provided through tooltips. Furthermore, the application offers
audio playback and zoom functionality.