A web application for filtering and annotating web speech data
David Lutz, Parry Cadwallader, Mats Rooth · eCommons (Cornell University) · 2013
A vast and growing amount of recorded speech is freely available on the web, including podcasts, radio broadcasts, and posts on media-sharing sites. However, finding specific words or phrases in online speech data remains a challenge for researchers, not least because transcripts of this data are often automatically-generated and imperfect. We have developed a web application, ?ezra?, that addresses this challenge by allowing non-expert and potentially remote annotators to filter and annotate speech data collected from the web and produce large, high-quality data sets suitable for speech research. We have used this application to filter and annotate thousands of speech tokens. Ezra is freely available on GitHub1, and development continues.