Constructing proximity graphs to explore similarities in large-scale melodic datasets

This paper investigates the construction of proximity graphs in order to allow users to explore similarities in melodic datasets. A key part of this investigation is the use of a multilevel framework for measuring similarity in symbolic musical representations. The basis of the framework is straightforward: initially each tune is normalised and then recursively coarsened, typically by removing weaker off-beats, until the tune is reduced to a skeleton representation with just one note per bar. Melodic matching can then take place at every level: the multilevel matching implemented here uses recursive variants of local alignment algorithms, but in principle a variety of similarity measures could be used. The multilevel framework is also exploited with the use of early termination heuristics at coarser levels, both to reduce computational complexity and, potentially, to enhance the matching qualitatively. The results of the matching algorithm are then used to construct proximity graphs which are displayed as part of an online interface for users to explore melodic similarities within a corpus of tunes

Tune classification using multilevel recursive local alignment algorithms

This paper investigates several enhancements to two well-established local alignment algorithms in the context of their use for melodic similarity. It uses the annotated dataset from the well-known Meertens Tune Collection to provide a ground truth and the research aim to answer the question, to what extent do these enhancements improve the quality of the algorithms? In the results, recursive application of the alignment algorithms, applied to a multilevel representation of the melodies, is shown to be very effective for improving the accuracy of the classification of the tunes into families. However, the ideas should be equally applicable to music search and melodic matching

A visual exploration of melodic relationships within traditional music collections

The aim of this paper is to discuss a technique for visually exploring melodic relationships within traditional tune collections encoded in abc notation, a widely used text-based music representation system particularly popular for folk and traditional music. There are approximately ½ million melodies encoded in abc on the web and abcnotation.com provides a searchable index of the entire corpus with tools to view, download and listen to the scores. This paper stems from related work known as TuneGraph which uses a melodic similarity measure to derive a proximity graph representing relationships between tunes in the abc corpus, and which allows users of abcnotation.com to explore melodic similarity. As it stands TuneGraph only gives a localised view of the melodic relationships: this paper aims to look at exploring those relationships at a global (corpus-based) level via a prototype visualisation tool. Currently the tool is not interactive: in this paper the aim is to consider a proof-of-concept approach to explore where there is a useful visualisation possible; future work will look at user interactivity with the tool

A statistical analysis of the ABC music notation corpus: exploring duplication

This paper presents a statistical analysis of the abc music notation corpus. The corpus contains around 435,000 transcriptions of which just over 400,000 are folk and traditional music. There is significant duplication within the corpus and so a large part of the paper discusses methods to assess the level of duplication and the analysis then indicates a headline figure of over 165,000 distinct folk and traditional melodies. The paper also describes TuneGraph, an online, interactive user interface for exploring tune variants, based on visualising the proximity graph of the underlying melodies

Partitioning Complex Networks via Size-constrained Clustering

The most commonly used method to tackle the graph partitioning problem in practice is the multilevel approach. During a coarsening phase, a multilevel graph partitioning algorithm reduces the graph size by iteratively contracting nodes and edges until the graph is small enough to be partitioned by some other algorithm. A partition of the input graph is then constructed by successively transferring the solution to the next finer graph and applying a local search algorithm to improve the current solution. In this paper, we describe a novel approach to partition graphs effectively especially if the networks have a highly irregular structure. More precisely, our algorithm provides graph coarsening by iteratively contracting size-constrained clusterings that are computed using a label propagation algorithm. The same algorithm that provides the size-constrained clusterings can also be used during uncoarsening as a fast and simple local search algorithm. Depending on the algorithm's configuration, we are able to compute partitions of very high quality outperforming all competitors, or partitions that are comparable to the best competitor in terms of quality, hMetis, while being nearly an order of magnitude faster on average. The fastest configuration partitions the largest graph available to us with 3.3 billion edges using a single machine in about ten minutes while cutting less than half of the edges than the fastest competitor, kMetis

The healing presence of art

The arts offer a broad range of historically-documented benefits to mental, physical and social health. UK-based charity Paintings in Hospitals was a pioneer of the modern “arts in health” movement and has provided arts services to willing healthcare partners for 60 years. Despite a large and continually-growing body of clinical evidence supporting the health benefits of the arts, and a recent parliamentary report suggesting that the arts could alleviate structural and financial stresses on health and social care services, resistance to nationwide integration of the arts with healthcare remains. The majority of this resistance stems from misunderstanding and misinformation that must be properly addressed before the “arts in health” sector is able to fulfil its potential

TuneGraph, an online visual tool for exploring melodic similarity

This paper presents TuneGraph, an online visual tool for exploring melodic similarity. The underlying data comes from a large index of online music, all transcribed in abc notation, and TuneGraph uses a melodic similarity metric to derive a proximity graph representing similarities within the index. A rich but dense graph is built and then sparsfied weak, non-essential edges. From this a local graph is extracted for each vertex, aimed at indicating close variants of, and similar melodies to, the underlying tune represented by the vertex. Finally an interactive user interface displays each local graph on that tune's webpage, allowing the user to explore melodically similar tunes

Roberto Gerhard: explorer and synthesist

There is a general perception that Gerhard’s late, modernist, style was due to a radical change of direction around the time of his First Symphony. This thesis argues that in fact several important elements integral to this ’new’ style are traceable in works as early as Dos apunts and Seven Haiku of 1921-22, and that during the intervening years Gerhard was exploring, expanding and accumulating the techniques which eventually enabled him to realise the potential of his sonic imagination. The first part of the thesis will discuss Gerhard’s origins in early twentieth century Catalonia, during the Catalan revival, with its modernisme and noucentisme, and the way in which these factors are reflected in his attitudes. In the second section the works selected will be placed in a biographical and musical context and analysed in order to demonstrate three aspects of his works. The first is that Gerhard approached each one as a separate exercise, using different methods in the most appropriate manner and disregarding questions of dogma. The second, that many of these techniques originate in the practices of the preceding generation, particularly Schoenberg, Stravinsky, Pedrell and Bartók, in addition to absorbing and applying significant elements from Catalan and Spanish traditional music. Comparators will be cited to demonstrate these facts. The final intent is to show that as the methods are applied they are explored and expanded to meet his own particular requirements and the resulting synthesis equipped him to realise their potential in his late style, fully exploited for the first time in the first movement of the First Symphony. This thesis deals with compositions preceding this work in order to demonstrate that despite the apparently disparate nature of Gerhard’s output between 1921 and 1953 there is a consistent attitude in his approach extending into the later stages of his life