Automatic evaluation of teacher speech level and student noise level in university classrooms

What is it about?

The background noise has a fundamental role in oral communication, since the higher the speech level with respect to the background noise the greater the intelligibility. In occupied lecture halls the main contribution to background noise is related to the human noise, which is called by scholars student activity. Scholars proposed methods to measure both student activity and speech level through short-time sound level meter measurements during lessons. However, a comparison of their relative effectiveness on a relevant set of data in different situations is still lacking. In this study, basing on recordings of university lessons performed with public address system, student activity and speech level values were extracted using different methods. Various scenarios of university lectures were recorded: frontal lessons, media-aided lectures, open discussions. Visual-segmentation and blind-segmentation procedures were compared for each case. Results show the benefits of blind-segmentation methods, which seem to be reliable and affordable methods for this kind of analyses.

Featured Image

Photo by Mikael Kristenson on Unsplash

Photo by Mikael Kristenson on Unsplash