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Hierarchical Bayesian Models for Audio and Music Processing

Hierarchical Bayesian Models for Audio and Music Processing

This video was recorded at NIPS Workshop on Music, Brain and Cognition, Whistler 2007 . In recent years, there has been an increasing interest in statistical approaches and tools from machine learning for the analysis of audio and music signals, driven partially by applications in music information retrieval, computer aided music education and interactive music performance systems. The application of statistical techniques is quite natural: acoustical time series can be conveniently modelled using hierarchical signal models by incorporating prior knowledge from various sources: from physics or studies of human cognition and perception. Once a realistic hierarchical model is constructed, many audio processing tasks such as coding, restoration, transcription, separation, identification or... Show More


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