- Vaclav Bouse
Multi-microphone based methods are used to enhance the performance of the distant-talking speech interfaces by exploiting spectral and spatial information of the relevant signals. When microphone arrays are employed for sampling acoustic wavefields, signal processing of the sensor data allows for spatial filtering which facilitates a better extraction of a desired source signal and suppression of unwanted interference signals such as competing speech from other passengers and car noise. Adaptive beamforming represents one class of such multichannel signal processing algorithms.
Adaptive beamforming algorithms such as the Robust Generalized Sidelobe Cancellor (RGSC) are of particular interest due to their ability to effectively suppress interfering signals while minimizing the distortion of the desired signal. The goal of this thesis is to investigate and possibly enhance the performance of the RGSC in the in-car scenario with respect to the attenuation of interfering speech and car noise using a minimum number of microphones. The performance of the RGSC will be evaluated utilizing signals from a database which contains recordings in a car under various speech and noise scenarios.
Investigations will be carried out using MATLAB and a comprehensive documentation of the code implemented is expected. A clear and concise write-up which describes the theory, realization and, results of the work done is of great importance.