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Robot audition and beat identification in noisy environments

David Grünberg, Daniel M. Lofaro, Paul Oh, Youngmoo E. Kim

Year
2011
Citations
6

Abstract

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.

Keywords

Computer scienceBeat (acoustics)Speech recognitionHumanoid robotNoise (video)RobotArtificial intelligenceAcoustics

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