LOCATION: TEL, Room Auditorium 3 (20th
floor), Ernst-Reuter-Platz 7, 10587 Berlin
David Rosson (TU Berlin)
The digitalisation of second language learning has been
developing for decades. With the boom of mobile devices, we see a
plethora of applications. The exploration of one sub-field, Computer
Assisted Pronunciation Training (CAPT), started just as early. In most
cases, however, the application of CAPT has not moved much beyond
audio-lingual (“listen and repeat”) exercises and acoustic
“scoring”. Can computers do more for learners than a “glorified
recorder”? Human experts with knowledge of phonetics are able to
listen to a recording and point out specific pronunciation errors and
give instructions on production. Can machines perform similar tasks?
This master thesis investigates the various aspects related to
detecting articulation events, and visualising demonstrative and
instructional information for the user in speech production exercises.
The exploration focuses on Web Audio APIs, open source feature
extraction libraries suitable for web applications, and digital signal
processing techniques including Dynamic Time Warping to provide
immediate feedback in an interactive environment.