A blackboard architecture for computational auditory scene analysis
A challenging problem for research in computational auditory scene analysis is the integration of evidence derived from multiple grouping principles. We describe a computational model which addresses this issue through the use of a `blackboard' architecture. The model integrates evidence from multiple grouping principles at several levels of abstraction, and manages competition between principles in a manner that is consistent with psychophysical findings. In addition, the blackboard architecture allows heuristic knowledge to influence the organisation of an auditory scene. We demonstrate that the model can replicate listeners' perception of interleaved melodies, and is also able to segregate melodic lines from polyphonic, multi-timbral audio recordings. The applicability of the blackboard architecture to speech processing tasks is also discussed.
blackboard auditory scene analysis computer model