| Summary: | In order for in-vehicle infotainment systems (IVISs) to be used using sound detection, it is important for the system to detect a strong and accurate signal. A direct sound source recorded is blended with a mixture of unwanted signal called noise from its surrounding where it does not represent the original sound sample. A clean voice must be obtained in order for the system to recognize the command from user without affecting its quality and to be interpreted precisely. Generally, sampling sound is obtained and matched to the pre-determined sample sound in the system. Unwanted range of signal is eliminated while retaining the expected sound source. In this project, the source taken into consideration is human's voice and white noise. White noise is chosen as it exhibits a random signal with a flat power spectral density which is use to represent the surrounding sound in car as well as sound produced from the engine. The technique used in separating the signal sources is based on Independent Component Analysis (ICA). In this project, method and strategy to separate driver's voice from another sound source has been discussed and the result shown that ICA method can be used to separate sound sources successfully.
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