An alignment based system for chord sequence retrieval

Hanna, Pierre; Robine, Matthias; Rocher, Thomas

doi:10.1145/1555400.1555417

Cited by 11 publications

(8 citation statements)

References 7 publications

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“…The systems currently known to us that are designed to match these sequences of symbolic chord descriptions are: the TPSD [3], the CSAS [4] and a harmony grammar approach [6]. The first two are quantitatively compared in this paper and are introduced in the next two subsections, respectively.…”

Section: Background: Similarity Measures For Chord Sequencesmentioning

confidence: 99%

“…However, we will show in this paper that they are also useful for retrieving pieces with a similar but not identical chord sequence by performing a large experiment. In this experiment we compare two harmonic similarity measures, the Tonal Pitch Step Distance (TPSD) [3] and the Chord Sequence Alignment System (CSAS) [4], and test the influence of different degrees of detail in the chord description and the knowledge of the global key of a piece on retrieval performance.…”

Section: Introductionmentioning

confidence: 99%

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Comparing Approaches to the Similarity of Musical Chord Sequences

Haas

Robine

Hanna

et al. 2011

Exploring Music Contents

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Abstract. We present an comparison between two recent approaches to the harmonic similarity of musical chords sequences. In contrast to earlier work, that mainly focuses on the similarity of musical scores or musical audio, in this paper we specifically use on the symbolic chord description as the primary musical representation and the similarity between sequences of these descriptions. In an experiment we compare a geometrical and an alignment approach to harmonic similarity, and measure the effects of chord description detail and a priori key information on retrieval performance. For this experiment a large new chord sequence corpus is assembled. The results show that a computational costly alignment approach significantly outperforms a much faster geometrical approach in most cases, that a priori key information boosts retrieval performance, and that using a triadic chord representation yields significantly better results than using more simple or more complex chord representations.

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Section: Background: Similarity Measures For Chord Sequencesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparing Approaches to the Similarity of Musical Chord Sequences

Haas

Robine

Hanna

et al. 2011

Exploring Music Contents

Self Cite

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“…On a melody classification task, he showed that expert-based heuristics could achieve almost perfect results. De Haas [87] showed that with regard to chord sequence similarity, local alignment with a substitution matrix based on simple heuristics [15], significantly outperforms his more sophisticated geometric model that takes into consideration the temporal relations between chords. Despite their success, the major concern with such approaches is their reliance on heuristics with known issues, such as limited generalization (see Section 1).…”

Section: Data-driven Modelling Of Global Similaritymentioning

confidence: 99%

Melodic Similarity and Applications Using Biologically-Inspired Techniques

et al. 2017

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Music similarity is a complex concept that manifests itself in areas such as Music Information Retrieval (MIR), musicological analysis and music cognition. Modelling the similarity of two music items is key for a number of music-related applications, such as cover song detection and query-by-humming. Typically, similarity models are based on intuition, heuristics or small-scale cognitive experiments; thus, applicability to broader contexts cannot be guaranteed. We argue that data-driven tools and analysis methods, applied to songs known to be related, can potentially provide us with information regarding the fine-grained nature of music similarity. Interestingly, music and biological sequences share a number of parallel concepts; from the natural sequence-representation, to their mechanisms of generating variations, i.e., oral transmission and evolution respectively. As such, there is a great potential for applying scientific methods and tools from bioinformatics to music. Stripped-down from biological heuristics, certain bioinformatics approaches can be generalized to any type of sequence. Consequently, reliable and unbiased data-driven solutions to problems such as biological sequence similarity and conservation analysis can be applied to music similarity and stability analysis. Our paper relies on such an approach to tackle a number of tasks and more notably to model global melodic similarity.

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“…Besides the distance measure that we will elaborate on in this paper, which was earlier introduced in [11,13], there exist two other methods that solely focus on the similarity of chord sequences: an alignment-based approach to harmonic similarity [14] and a grammatical parse tree matching method [12]. The first two are quantitatively compared in in Sect.…”

Section: Harmonic Similarity Measuresmentioning

confidence: 99%

“…The chord sequence alignment system (CSAS) [14] is based on local alignment and computes similarity between two sequences of symbolic chord labels. By performing elementary operations, the one chord sequence is transformed into the other chord sequence.…”

Section: Harmonic Similarity Measuresmentioning

confidence: 99%

A geometrical distance measure for determining the similarity of musical harmony

Haas

Wiering

Veltkamp

2013

Int J Multimed Info Retr

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In the last decade, digital repositories of music have undergone an enormous growth. Therefore, the availability of scalable and effective methods that provide contentbased access to these repositories has become critically important. This study presents and tests a new geometric distance function that quantifies the harmonic distance between two pieces of music. Harmony is one of the most important aspects of music and we will show in this paper that harmonic similarity can significantly contribute to the retrieval of digital music. Yet, within the music information retrieval field, harmonic similarity measures have received far less attention compared to other similarity aspects. The distance function we present, the Tonal pitch step distance, is based on a cognitive model of tonality and captures the change of harmonic distance to the tonal center over time. This distance is compared to two other harmonic distance measures. We show that it can be efficiently used for retrieving similar chord sequences, and that it significantly outperforms a baseline string matching approach. Although the proposed method is not the best performing distance measure, it offers the best quality-runtime ratio. Furthermore, we demonstrate in a case study how our harmonic similarity measure can contribute to the musicological discussion of the melody and harmony in large-scale corpora.

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An alignment based system for chord sequence retrieval

Cited by 11 publications

References 7 publications

Comparing Approaches to the Similarity of Musical Chord Sequences

Comparing Approaches to the Similarity of Musical Chord Sequences

Melodic Similarity and Applications Using Biologically-Inspired Techniques

A geometrical distance measure for determining the similarity of musical harmony

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