Pattern Discovery Techniques for Music Audio

Pattern Discovery Techniques for Music Audio

Human listeners are able to recognize structure in music through the perception of repetition and other relationships within a piece of music. This work aims to automate the task of music analysis. Music is “explained” in terms of embedded relationships, especially repetition of segments or phrases. The steps in this process are the transcription of audio into a representation with a similarity...

Segmental Pattern Discovery in Music

I this paper we describe a new method for discovering recurrent patterns in a corpus of segmented melodies. Elements of patterns in this scheme do not represent individual notes but rather represent melodic segments that are sequences of notes. A new knowledge representation for segmental patterns is designed, and a pattern discovery algorithm based on suffix trees is used to discover segmental...

Music Pattern Discovery with Variable Markov Oracle: A Unified Approach to Symbolic and Audio Representations

This paper presents a framework for automatically discovering patterns in a polyphonic music piece. The proposed framework is capable of handling both symbolic and audio representations. Chroma features are post-processed with heuristics stemming from musical knowledge and fed into the pattern discovery framework. The pattern-finding algorithm is based on Variable Markov Oracle. The Variable Ma...

Large-Scale Pattern Discovery in Music

Large-Scale Pattern Discovery in Music Thierry Bertin-Mahieux This work focuses on extracting patterns in musical data from very large collections. The problem is split in two parts. First, we build such a large collection, the Million Song Dataset, to provide researchers access to commercial-size datasets. Second, we use this collection to study cover song recognition which involves finding ha...

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