Automaatne tonaalsuse avastamine
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Date
2011
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Publisher
Tartu Ülikool
Abstract
Selles töös oleme pakkunud mudeli tonaalsuse avastamiseks, mis on võimeline tegelema muusikaga erinevatest muusikalisest traditsioonedest ilma, et nende põhjalik analüüs oleks nõutud. Meie mudel põhineb eeldusel, et enamik muusikalisi traditsioone kasutavad hieraarhia kehtestaniseks helide kestust. Oleme pakkunud algoritmi automaatseks helilaadi avastamiseks.
Meetod oli hinnatud nii sümboolse kui ka audio andmestiku peal.
In this thesis we have proposed a model for tonality estimation, which is capable of handling music coming from various musical traditions and does not require their thorough analysis. In our model we have employed an assumption, that most musical traditions use duration to maintain pitch salience. Proceeding from this assumption, we have proposed an algorithm for automatic key detection, based on a distributional approach. The proposed method was evaluated on both symbolic and acoustic datasets.
In this thesis we have proposed a model for tonality estimation, which is capable of handling music coming from various musical traditions and does not require their thorough analysis. In our model we have employed an assumption, that most musical traditions use duration to maintain pitch salience. Proceeding from this assumption, we have proposed an algorithm for automatic key detection, based on a distributional approach. The proposed method was evaluated on both symbolic and acoustic datasets.