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My system uses an interactive genetic algorithm to learn a user's criteria for the task of generating musical rhythms. Interactive genetic algorithms (Smith 91) are well suited to solving this problem because they allow for a user to simply execute fitness functions (that is, to choose which rhythms or features of rhythms he likes), without necessarily(More)
We describe Aardvark, a social search engine. With Aardvark, users ask a question, either by instant message, e-mail, Web input, text message, or voice. Aardvark then routes the question to the person in the user's extended social network most likely to be able to answer that question. As compared to a traditional Web search engine, where the challenge lies(More)
The evaluation of the degree of speech impairment and the utility of computer recognition of impaired speech are separately and independently performed. Particular attention is paid to the question concerning whether or not there is a relationship between naive listeners' subjective judgements of impaired speech and the performance of a laboratory version(More)
This study investigated possible similarities between the ability to identify pitches and the ability to identify loudnesses. Systematic training of musically naive subjects indicated that frequency identification performance improves at about the same rate as intensity identification performance. Examination of frequency and intensity identification(More)
This thesis presents an approach to building more intelligent computer music systems. Motivated by the shortcomings of previous systems, I maintain that an enumeration and quantification of musical common sense concepts is necessary for the construction of musically intelligent systems. Demonstrating this approach, a computer system for analyzing and(More)
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