Robot audition and beat identification in noisy environments
David Grünberg, Daniel M. Lofaro, Paul Oh, Youngmoo E. Kim · 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems · 2011
In pursuit of our long-term goal of developing an interactive humanoid musician, we are developing robust methods to determine musical beat locations from live acoustic sources. A variety of beat tracking systems have been previously developed, but for the most part they are optimized for direct audio input (no acoustic channel and no noise). The presence of an acoustic channel and noise typically degrades performance substantially. A robot's motors, in particular, create nonstationary noise that can be difficult for a beat detection system to accommodate, Using an algorithm previously developed by the authors, we explore techniques for reducing the effects of the acoustic channel and noise on the system, enabling a humanoid to robustly follow music under realistic conditions.