Interactive Music Summarization Based on Generative Theory of Tonal Music

This paper presents an algorithm that checks for melodic similarity and a music summarization system called “Papipuun.” First, we developed a data structure for representing polyphony based on a time-span reduction in the generative theory of tonal music (GTTM) and the deductive object-oriented database (DOOD). A least upper bound operation is introduced to check the similarity of polyphonies represented in our method. Next, Papipuun performs quick listening in a manner similar to stylus skipping on a scratched record, but the skipping occurs correctly at punctuations of musical phrases, not arbitrarily. Papipuun can produce a music summary of good quality with a symbolic approach, reflecting the atmosphere of an entire piece through interaction with the user. In a pre-processing phase of Papipuun, a user analyzes an input piece by time-span reduction, using a dedicated tool called TS-Editor. For the real-time phase, the user interacts with the main system, Summarizer, to perform music summarization. The summarizer ascertains a piece structure by similarity checking. When the user identifies fragments to be skipped, Summarizer deletes them and concatenates the rest

Active listening · Automatic summarization · Generative grammar · Melody · Musical · Polyphony · Speech recognition · Computer Science · Mathematics · Music and Audio Processing · Music Technology and Sound Studies · Neuroscience and Music Perception · Artificial Intelligence

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