Noise Reduction for Driver-To-Pit-Crew Communication in Motor Racing

This work proposes a noise reduction system for use in high noise environments such as motor racing. First, an analysis of the audio data received from the driver reveals that the main noise sources are from the engine, airflow and tyres. These are found to relate to engine speed, road speed and throttle position information that is received in a data stream from the car´s on-board computer. A two-stage noise compensation strategy is proposed which first suppresses engine harmonics using adaptive filtering with engine speed reference information taken from the data stream. Second, a maximum a posteriori (MAP) prediction of the tyre and airflow noise is made from data stream values and this is combined with spectral subtraction for noise suppression. Human listening tests reveal that both noise reduction stages lead to good improvements in the intelligibility of the speech with a comparative mean opinion score (CMOS) of + 1.57 being obtained