Melodic Identification Using Probabilistic Tree Automata

Bernabeu, José F.; Calera-Rubio, Jorge; Iñesta, José M.; Rizo, David

doi:10.1080/09298215.2011.573560

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…Using hierarchical models is a trend sucessfully explored for rhythmic notation processing e.g. [17,1,10], meter detection [14], melodic search [3], and music analysis [7,19,15,13]. The approach is founded on the conviction that music structure complexity exceeds linear models.…”

Section: Discussionmentioning

confidence: 99%

A Parse-Based Framework for Coupled Rhythm Quantization and Score Structuring

Foscarin

Jacquemard

Rigaux

et al. 2019

Mathematics and Computation in Music

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We present a formal language-based framework for MIDI-toscore transcription, the problem of converting a sequence of symbolic musical events with arbitrary timestamps into a structured music score. The framework aims at solving in one pass the two subproblems of rhythm quantization and score production. It relies, throughout the process, on an apriori hierarchical model of scores given by generative grammars. We show that this coupled approach helps to make relevant and interrelated decisions, and we present an algorithm computing transcription solutions optimal with respect to both the fitness of the quantization to the input, and a measure of complexity of music notation.

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Section: Discussionmentioning

confidence: 99%

A Parse-Based Framework for Coupled Rhythm Quantization and Score Structuring

Foscarin

Jacquemard

Rigaux

et al. 2019

Mathematics and Computation in Music

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“…The same hierarchical structure type was used by Jacquemard et al [13] for elegantly representing and transforming rhythm notation (see Figure 5). With the objective of measuring the similarity of music, metric tree structures were introduced by Rizo [24] (see Figure 6) and extended with k-testables by Bernabeu et al [1]. With the same purpose, Pinto and Tagliolato [23] proposed a graph representation of melodic sequences (see Figure 7).…”

Section: Hierarchical Analysis and Representationmentioning

confidence: 99%

A standard format proposal for hierarchical analyses and representations

Rizo

Marsden

2016

Proceedings of the 3rd International Workshop on Digital Libraries for Musicology

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In the realm of digital musicology, standardizations efforts to date have mostly concentrated on the representation of music. Analyses of music are increasingly being generated or communicated by digital means. We demonstrate that the same arguments for the desirability of standardization in the representation of music apply also to the representation of analyses of music: proper preservation, sharing of data, and facilitation of digital processing. We concentrate here on analyses which can be described as hierarchical and show that this covers a broad range of existing analytical formats. We propose an extension of MEI (Music Encoding Initiative) to allow the encoding of analyses unambiguously associated with and aligned to a representation of the music analysed, making use of existing mechanisms within MEI's parent TEI (Text Encoding Initiative) for the representation of trees and graphs.

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“…These models are worth describing here in more detail because they illustrate clearly the importance of interpretation, to be discussed below. Rizo (2010) and Bernabeu et al (2009) derive the reduction of a melody by selecting one of the notes occurring in each span based on a small number of rules. The spans are determined by the metre, so that, in 4/4 for example, there is a span for each bar, at the next level down two spans for the minims (half notes), then four spans for the crotchets (quarter notes), etc., halving each span at the level above.…”

Section: Models Of Similaritymentioning

confidence: 99%

Interrogating Melodic Similarity: A Definitive Phenomenon or the Product of Interpretation?

Marsden

2012

Journal of New Music Research

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The nature of melodic similarity is interrogated through a survey of the different means by which the phenomenon has been studied, examination of methods for measuring melodic similarity, a Monte Carlo analysis of data from the experiment which formed the basis for the 'ground truth' used in the MIREX 2005 contest on melodic similarity, and examples of interest in the music of Mozart. Melodic similarity has been studied by a number of means, sometimes quite contrasting, which lead to important differences in the light of the finding that similarity is dependent on context. Models of melodic similarity based on reduction show that the existence of multiple possible reductions forms a natural basis for similarity to depend on interpretation. Examination of the MIREX 2005 data shows wide variations in subjects' judgements of melodic similarity and some evidence that the perceived similarity between two melodies can be influenced by the presence of a third melody. Examples from Mozart suggest that he deliberately exploited the possibilities inherent in recognising similarity through different interpretations. It is therefore proposed that similarity be thought of not as a distinct and definite function of two melodies but as something created in the minds of those who hear the melodies.

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Melodic Identification Using Probabilistic Tree Automata

Cited by 6 publications

References 20 publications

A Parse-Based Framework for Coupled Rhythm Quantization and Score Structuring

A Parse-Based Framework for Coupled Rhythm Quantization and Score Structuring

A standard format proposal for hierarchical analyses and representations

Interrogating Melodic Similarity: A Definitive Phenomenon or the Product of Interpretation?

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