For virtual and augmented reality applications, it is desirable to render audio sources in the space the user is in, in real-time without sacrificing the perceptual quality of the sound. One aspect of the rendering that is perceptually important for a listener is the late-reverberation, or \echo", of the sound within a room environment. A popular method of generating a plausible late-reverberation in real-time is the use of Feedback-Delayed Network (FDN). However, its use has the drawback that it first has to be tuned (usually manually) for a particular room before the late-reverberation generated becomes perceptually accurate. In this thesis, we propose a data-driven approach to automatically generate a pre-tuned FDN for any given room described by a set of room parameters. When combined with existing method for rendering the direct path and early reflections of a sound source, we demonstrate the feasibility of being able to render audio source in real-time.

 

                           Chair:              Dr. Ramani Duraiswami     
                          Members:        Dr. Matthias Zwicker  
                                                     Dr. Nirupam Roy