Abstract

We evaluate a variety of audio recording techniques for a project on the automatic analysis of speech dialog in middle school and high school classrooms. In our scenario, the teacher wears a headset microphone or a lapel microphone. A second microphone is then used to collect speech and related sounds from students in the classroom. Various boundary microphones, omni-directional microphones, and cardioid microphones are tested as this second classroom microphone. A commercial microphone array [Microsoft Xbox Kinect] is also tested. We report on how well digital source-separation techniques work for segregating the teacher and student speech signals from one another based on these various microphones and placements. We also test the recordings using various automatic speech recognition engines for word recognition error rates under different levels of background noise. Preliminary results indicate one boundary microphone, the Crown PZM-30, to be superior for the classroom recordings. This is based on its performance at capturing near and distant student signals for ASR in noisy conditions, as measured by ASR error rates across different ASR engines.

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