Applications of Algorithmically-Generated Digital Audio for Web-Based Sonic Measure Ear Training
This paper examines applications of algorithmically-generated digital audio for a new type of ear training. This approach, called sonic measure ear training, circumvents the many limits of MIDI-based aural testing, and may offer a valuable resource for computer musicians and audio engineers. The Post-Ut system, introduced here, is the first web-based ear training system to offer sonic measure ear-training. After describing the design of the Post-Ut system, including the use of athenaCL, Csound, Python, and MySQL, the audio generation procedures are examined in detail. The design of questions and perceptual considerations are evaluated, and practical applications and opportunities for future development are outlined.
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