Big Chord Data Extraction and Mining

Harmonic progression is one of the cornerstones of tonal music composition and is thereby essential to many musical styles and traditions. Previous studies have shown that musical genres and composers could be discriminated based on chord progressions modeled as chord n-grams. These studies were however conducted on small-scale datasets and using symbolic music transcriptions. In this work, we apply pattern mining techniques to over 200,000 chord progression sequences out of 1,000,000 extracted from the I Like Music (ILM) commercial music audio collection. The ILM collection spans 37 musical genres and includes pieces released between 1907 and 2013. We developed a single program multiple data parallel computing approach whereby audio feature extraction tasks are split up and run simultaneously on multiple cores. An audio-based chord recognition model (Vamp plugin Chordino) was used to extract the chord progressions from the ILM set. To keep low-weight feature sets, the chord data were stored using a compact binary format. We used the CM-SPADE algorithm, which performs a vertical mining of sequential patterns using co-occurence information, and which is fast and efficient enough to be applied to big data collections like the ILM set. In orderto derive key-independent frequent patterns, the transition between chords are modeled by changes of qualities (e.g. major, minor, etc.) and root keys (e.g. fourth, fifth, etc.). The resulting key-independent chord progression patterns vary in length (from 2 to 16) and frequency (from 2 to 19,820) across genres. As illustrated by graphs generated to represent frequent 4-chord progressions, some patterns like circle-of-fifths movements are well represented in most genres but in varying degrees. These large-scale results offer the opportunity to uncover similarities and discrepancies between sets of musical pieces and therefore to build classifiers for search and recommendation. They also support the empirical testing of music theory. It is however more difficult to derive new hypotheses from such dataset due to its size. This can be addressed by using pattern detection algorithms or suitable visualisation which we present in a companion study

Logic-based Modelling of Musical Harmony for Automatic Characterisation and Classification

The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the authorMusic like other online media is undergoing an information explosion. Massive online music stores such as the iTunes Store1 or Amazon MP32, and their counterparts, the streaming platforms, such as Spotify3, Rdio4 and Deezer5, offer more than 30 million6 pieces of music to their customers, that is to say anybody with a smart phone. Indeed these ubiquitous devices offer vast storage capacities and cloud-based apps that can cater any music request. As Paul Lamere puts it7: “we can now have a virtually endless supply of music in our pocket. The ‘bottomless iPod’ will have as big an effect on how we listen to music as the original iPod had back in 2001. But with millions of songs to chose from, we will need help finding music that we want to hear [...]. We will need new tools that help us manage our listening experience.” Retrieval, organisation, recommendation, annotation and characterisation of musical data is precisely what the Music Information Retrieval (MIR) community has been working on for at least 15 years (Byrd and Crawford, 2002). It is clear from its historical roots in practical fields such as Information Retrieval, Information Systems, Digital Resources and Digital Libraries but also from the publications presented at the first International Symposium on Music Information Retrieval in 2000 that MIR has been aiming to build tools to help people to navigate, explore and make sense of music collections (Downie et al., 2009). That also includes analytical tools to suppor

Improving music genre classification using automatically induced harmony rules

We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which for each chord the degree and chord category are identified, and covering classical, jazz and pop genre classes. The audio descriptor-based genre classifier contains 206 features, covering spectral, temporal, energy, and pitch characteristics of the audio signal. The fusion of the harmony-based classifier with the extracted feature vectors is tested on three-genre subsets of the GTZAN and ISMIR04 datasets, which contain 300 and 448 recordings, respectively. Machine learning classifiers were tested using 5 × 5-fold cross-validation and feature selection. Results indicate that the proposed harmony-based rules combined with the timbral descriptor-based genre classification system lead to improved genre classification rates

Improving music genre classification using automatically induced harmony rules

We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which for each chord the degree and chord category are identified, and covering classical, jazz and pop genre classes. The audio descriptor-based genre classifier contains 206 features, covering spectral, temporal, energy, and pitch characteristics of the audio signal. The fusion of the harmony-based classifier with the extracted feature vectors is tested on three-genre subsets of the GTZAN and ISMIR04 datasets, which contain 300 and 448 recordings, respectively. Machine learning classifiers were tested using 5 × 5-fold cross-validation and feature selection. Results indicate that the proposed harmony-based rules combined with the timbral descriptor-based genre classification system lead to improved genre classification rates

Representing chord sequences in OWL

Chord symbols and progressions are a common way to describe musical harmony. In this paper we present SEQ, a pattern representation using the Web Ontology Language OWL DL and its application to modelling chord sequences. SEQ provides a logical representation of order information, which is not available directly in OWL DL, together with an intuitive notation. It therefore allows the use of OWL reasoners for tasks such as classification of sequences by patterns and determining subsumption relationships between the patterns. The SEQ representation is used to express distinctive pattern obtained using data mining of multiple viewpoints of chord sequences

The Other Sides of Billy Joel: Six Case Studies Revealing the Sociologist, the Balladeer, and the Historian

The failure of music critics to recognize Billy Joel’s tendency towards writing songs about issues greater than himself, issues such as the Vietnam War, the Cold War, struggling American industries and the effect of mass media on popular culture, particularly on two albums, The Nylon Curtain and Storm Front, has led to a pronounced lacuna in serious scholarship on Joel and his music. Relegated to adult contemporary radio stations due to the success of romantic pop ballads such as “Just the Way You Are,” “She’s Always a Woman” and “Uptown Girl,” and derided as a drunken egomaniac by many reviewers, Joel has thus far been largely ignored by the academic world. The greater part of Joel’s oeuvre supports these assumptions, as the majority of his creative output focuses on his life, both romantic and professional. Careful analysis of six songs, however, three from each of the aforementioned albums (“Pressure,” “Goodnight Saigon,” and “Allentown” from The Nylon Curtain and “We Didn’t Start the Fire,” “Leningrad,” and “The Downeaster ‘Alexa’” from Storm Front) reveal Joel, for perhaps the only times in his lengthy career, placing the priorities and needs of his audience before his own. The result is a pair of albums (and three pairs of songs) that stand out from the remainder of his output in terms of social relevance. In these six songs, Joel adopted new roles, roles that he had previously eschewed. In “Pressure” and “We Didn’t Start the Fire,” Joel becomes a sociologist, commenting on the societal effects of pop culture. “Goodnight Saigon” and “Leningrad” address the two great wars of Joel’s lifetime, the Vietnam War and the Cold War, while “Allentown” and “The Downeaster ‘Alexa’” provide narratives on the decline of the Pennsylvania steel industry and the North Atlantic fishery, respectively. Joel’s evolution as both a songwriter and a global citizen becomes apparent through close examination of these six songs and the albums on which they appear, and their respective videos, revealing Joel’s songwriting powers at their peak and his groundbreaking approach to the art of video-making

Hammond Technique and Methods: Music Written for the Hammond Organ

The following thesis is made up of four original compositions written between February and September of 2012, with emphasis on the Hammond Organ in the context of jazz and rhythm and blues ensembles. The pieces of music were designed to feature the organ as the lead instrument in order to highlight various playing techniques that are specific to the Hammond Organ within these genres. In addition to my own music and an explanation and analysis of my work, the writing will provide a historical overview of organists I have chosen to highlight as influences to provide a framework for each piece of music. In order to aid this discussion of what has been an under-theorized instrument and performance tradition, I have sought out active contemporary organists to discuss their creative practices on the Hammond, as well as their insight into the notable organists of the past. Finally, of particular interest to me in this thesis is the emphasis on the Hammond Organ as an electric instrument, and the unique musical textures that are possible through the exploitation of the multiple controls that are integral to the instrument's construction. An audio recording of each piece accompanies the scores that are included

Towards automatic extraction of harmony information from music signals

PhDIn this thesis we address the subject of automatic extraction of harmony information from audio recordings. We focus on chord symbol recognition and methods for evaluating algorithms designed to perform that task. We present a novel six-dimensional model for equal tempered pitch space based on concepts from neo-Riemannian music theory. This model is employed as the basis of a harmonic change detection function which we use to improve the performance of a chord recognition algorithm. We develop a machine readable text syntax for chord symbols and present a hand labelled chord transcription collection of 180 Beatles songs annotated using this syntax. This collection has been made publicly available and is already widely used for evaluation purposes in the research community. We also introduce methods for comparing chord symbols which we subsequently use for analysing the statistics of the transcription collection. To ensure that researchers are able to use our transcriptions with confidence, we demonstrate a novel alignment algorithm based on simple audio fingerprints that allows local copies of the Beatles audio files to be accurately aligned to our transcriptions automatically. Evaluation methods for chord symbol recall and segmentation measures are discussed in detail and we use our chord comparison techniques as the basis for a novel dictionary-based chord symbol recall calculation. At the end of the thesis, we evaluate the performance of fifteen chord recognition algorithms (three of our own and twelve entrants to the 2009 MIREX chord detection evaluation) on the Beatles collection. Results are presented for several different evaluation measures using a range of evaluation parameters. The algorithms are compared with each other in terms of performance but we also pay special attention to analysing and discussing the benefits and drawbacks of the different evaluation methods that are used

"Get Listenin' Kids!": Independence as Social Practice in American Popular Music

This dissertation examines the concept of independence--defined as alternative approaches to the creation, distribution and consumption of music that actively resist cultural hegemonies--as an ongoing tradition in American popular music. While previous studies of independence have focused on specific independent record labels or eras, this project views independence as a historical trajectory that extends to the beginnings of the recording industry. Pierre Bourdieu's concept of the social field frames my investigation of the ways in which independence becomes socially and musically manifested in communities of musicians, mediators and audiences. I explore how these communities articulate their distinction within the dominant music industry by responding to the social and aesthetic chasms created by the centralization of media. This study is divided into two sections. The first focuses on independent record labels and local radio broadcasts in the first half of the twentieth century, when "independent" referred to either a record label that distributed outside major label channels, or a radio station unaffiliated with a network. In the second section, I show how the modern concept of independence became more overtly political with the emergence of the punk movement of the late 1970s. I follow the subsequent development of independent underground networks in the 1980s through their present-day fragmentation in twenty-first century internet culture. I conclude with an ethnographic examination of independent music performances in order to show that, while independence remains situated in ideas about community, authenticity and autonomy, it is subjectively understood and constructed by individual members of independent communities. The primary research for this study draws from eight years of personal experience as a freeform DJ and active consumer of independent music, as well as seven years working as a sound archivist at the University of Maryland Broadcasting Archives. Because this is a study of popular music, I engage with several interdisciplinary theoretical areas, including ethnomusicology, musicology, sociology and media studies, in order to conceptualize some of the patterns that shape independent social practices

Three Solitudes and a DJ: A Mashed-up Study of Counterpoint in a Digital Realm

This dissertation is primarily concerned with developing an understanding of how the use of pre-recorded digital audio shapes and augments conventional notions of counterpoint. It outlines a theoretical framework for analyzing the contrapuntal elements in electronically and digitally composed musics, specifically music mashups, and Glenn Gould’s Solitude Trilogy ‘contrapuntal radio’ works. Conventional studies of counterpoint encompass sixteenth- through early twentieth-century modernist and neo- classical materials but stop there. Composition by magnetic tape and computer software using pre-existing recorded audio offers the potential for a new study of music that displays clear contrapuntal elements but lacks the analytical models to outline the underlying musical systems. Central to these investigations is the assertion that counterpoint operates not only within the sphere of art music but also in the compositional logic of non-musical sound works (radio documentary) and in the harmonic and melodic underpinnings of popular music. The first chapter examines technological and cultural developments that contribute to the formation of digital contrapuntal music. The second and third chapters outline the traditional musical elements—harmony, form, and texture—of contrapuntal radio and mashups, respectively. Chapter Four explores how counterpoint exists in the sonic space of the stereo or mono sound field. Chapter Five presents the notion of program as a useful concept for analyzing interaction between lyric samples to form original narratives. These two final chapters present the original contributions from contrapuntal radio and mashups to a study of counterpoint. In each of these chapters, counterpoint forms the basis for how we perceive the underlying systems of musical works composed by traditional counterpoint or by assembling pre-existing recorded audio. The connection between the old and new is important, as one does not supplant but augment the other. As such, counterpoint is a fluid musical concept, rather than a fixed system of rules governing composition in a narrow musical palette