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A coupled duration-focused architecture for realtime music to score alignment

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text
 

Genre(s)

article
 

Forme(s)

document numérique
 

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Titre

A coupled duration-focused architecture for realtime music to score alignment
 

Nom(s)

Cont, Arshia (auteur)
 

Publication

2010
 

Description

Sujet(s)

Score Following   Anticipatory Systems   Real-time systems   Hidden Markov Models   Duration Models   Antescofo
 

Résumé

The capacity for realtime synchronization and coordination is a common ability among trained musicians performing a music score that presents an interesting challenge for machine intelligence. Compared to speech recognition, which has influenced many music information retrieval systems, music's temporal dynamics and complexity pose challenging problems to common approximations regarding time modeling of data streams. In this paper, we propose a design for a realtime music to score alignment system. Given a live recording of a musician playing a music score, the system is capable of following the musician in realtime within the score and decoding the tempo (or pace) of its performance. The proposed design features two coupled audio and tempo agents within a unique probabilistic inference framework that adaptively updates its parameters based on the realtime context. Online decoding is achieved through the collaboration of the coupled agents in a Hidden Hybrid Markov/semi-Markov framework where prediction feedback of one agent affects the behavior of the other. We perform evaluations for both realtime alignment and the proposed temporal model. An implementation of the presented system has been widely used in real concert situations worldwide and the readers are encouraged to access the actual system and experiment the results.
 

Note(s)

Article paru dans : IEEE Transaction on Pattern Analysis and Machine Intelligence vol. 32 n°6
 

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Date de la notice

2011-09-08 02:00:00
 

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