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 us e of a 'blackboard' architecture. The model integrates evidence from multip le grouping principles at several levels of abstraction, and manages compet ition between principles in a manner that is consistent with psychophysical findings. In addition, the blackboard architecture allows heuristic knowle dge 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 aud io recordings. The applicability of the blackboard architecture to speech p rocessing tasks is also discussed. (C) 1999 Elsevier Science B.V. All right s reserved.