Two generic mechanisms are proposed that facilitate the efficient integration of audio content analysis algorithms. The first mechanism, priority-rule based interleaving of algorithms, allows the simultaneous interoperation of several bottom-up analysis modules by interleaving their atomic steps. It aims at increased accuracy through controlled manipulation of common data. The second mechanism, top-down routing of requests for data, allows high-level predictions to direct the bottom-up analysis towards verifying the predicted hypotheses by observations. Examples from automatic music transcription are presented to clarify the use of the proposed methods.
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