Subject: Re: Design and language for CASA implementation From: Klapuri Anssi <klap(at)CS.TUT.FI> Date: Tue, 29 Apr 2003 09:02:34 +0300Dear Andrew, You wrote: >I am currently in the process of designing an architecture for a CASA >system for automatic transcription of music. I know that many people I recommend dynamic Bayesian networks (DBN) for this purpose. See for example (available online) Dynamic Bayesian Networks (Draft) To appear in Probabilistic Graphical Models, Michael Jordan. Kevin Murphy. November 2002. Maybe you would not call DBNs a software "architecture", but for me at least, it has provided exactly the kind of framework that is needed for integrating knowledge from different sources (acoustic data, internal models, musicological models etc.). Probability theory is a solid "common ground" for integrating knowledge and has served excellently in speech recognition. I have designed one blackboard architecture in Klapuri. "Means of integrating audio content analysis algorithms". 110th Audio Engineering Society Convention, Amsterdam, Netherlands, 2001. (available http://www.cs.tut.fi/~klap/iiro/index.html) but personally, I nowadays ***discourage*** using blackboard architectures. Matters of implementation easily distract from thinking about the model-level framework. Especially many young researchers (me included) have simply wasted time with artificial-intelligence architectures (implementation) before thinking about the computational theory and the algorithm for attaining the desired analysis. There is one approach to automatic transcription of music which is still largely unexplored. That is the redundant approach (see e.g. Bregman in "Computational auditory scene analysis," Rosenthal, Okuno (Eds)), where ***a lot*** of simple algorithms that try to attain a same goal are put together. I am meaning tens of bottom-up and top-down heuristics. In this case (and maybe only here), the architecture plays a crucial role. --Anssi ___________________________________________________________________________ Anssi Klapuri klap(at)cs.tut.fi http://www.cs.tut.fi/~klap Rongankatu 11 C 61, 33100 Tampere, Finland Tampere University of Tech., P.O.Box 553, FIN-33101 Tampere, Finland +358-3-3115 2124/-4954(work,fax) +358-3-2145252(home) +358-50-3648208(gsm)