Xavier Domont, "Study of Blind Dereverberation Algorithms for Real-Time Applications", 2005.

At Honda Research Institute Europe, an automatic speech recognition system is developed for the humanoid robot ASIMO. The reverberation effect alters the perception of speech signals emitted in a room and reduces the performance of automatic speech recognition. A lot of methods have been proposed in the past few decades to enhance reverberant speech signals. This diploma thesis studies the most promising algorithms and discusses if they can be implemented in realtime for real environments. The existing methods can be classified in two families: 1. Those who estimate directly the clean speech signal and treat reverberations as disturbances. 2. Those who estimate the room impulse response and invert the estimated system to recover the clean speech. These two approaches are compared in this thesis, based on implementations in Matlab of selected algorithms. The focus of this comparison is set on the suitability of these algorithms for real environments, where speaker and robot are moving, and a possible real-time implementation.