Villarreal, Daniel
(2023)
Archive of Pittsburgh Language and Speech.
In: Pitt Momentum Fund 2023.
Abstract
As research methods develop amid the current data science epoch, new and under-resourced researchers find it increasingly difficult to keep up. Open Science research tools like the R programming language are touted as democratizing research; however, these tools can themselves impose a barrier to entry, widening the gap between well-resourced and under-resourced researchers (Villarreal & Collister forthcoming). At Pitt, we're sitting on a trove of Pittsburgh speech data that has yielded research influential in sociolinguistics (Johnstone, Andrus & Danielson 2006; Johnstone & Kiesling 2008). The proposed project transforms this data into the Archive of Pittsburgh Language and Speech (APLS). While Open Data is an emerging trend in sociolinguistics (Kendall & Farrington 2020; Stanford forthcoming), APLS will be the most powerful such resource yet. APLS will be powered by the linguistic data software LaBB-CAT (Fromont & Hay 2012), which performs automatic tagging of speech data through machine-learning methods, allows researchers to rapidly search for patterns of interest, and can directly interface with programming languages like R and Python. Future directions include training materials and outreach so APLS is accessible to wide audiences of researchers. Efforts like these are essential if Open Science is to be actually open to all.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
Metrics
Monthly Views for the past 3 years
Plum Analytics
Altmetric.com
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}