In-vehicle speech recognition and tutorial keywords spotting for novice drivers' performance evaluation

Novice young drivers are more frequently involved in traffic accidents, and studies have shown that effective supervised driver training is the key in reducing young drivers' risks. Using our previously developed Mobile-UTDrive in-vehicle data acquisition platform, two 16-age novice drivers participated in naturalistic drive training data collection. This paper focuses on analysis of novice driver training signals from an audio processing perspective. Specifically, analysis of supervised driver instruction audio and resulting CAN-Bus maneuver operation is performed. Following a procedure which consists of noise suppression, speech recognition and keyword spotting, five tutorial keywords - Brake, Gas, Left, Right and Stop - are spotted at an overall accuracy rate of 40% versus all spontaneous continuous speech. The time stamps of these keywords are then used as indications of driving maneuvers. As examples of driving performance evaluation, the case of making Left-Turn maneuvers for the two novice drivers are assessed and compared, and the increase of driving skills over experiences are analyzed.