Automatic Transcription of Bass Guitar Tracks applied for Music Genre Classification and Sound Synthesis

Musiksignale bestehen in der Regel aus einer Überlagerung mehrerer Einzelinstrumente. Die meisten existierenden Algorithmen zur automatischen Transkription und Analyse von Musikaufnahmen im Forschungsfeld des Music Information Retrieval (MIR) versuchen, semantische Information direkt aus diesen gemischten Signalen zu extrahieren. In den letzten Jahren wurde häufig beobachtet, dass die Leistungsfähigkeit dieser Algorithmen durch die Signalüberlagerungen und den daraus resultierenden Informationsverlust generell limitiert ist. Ein möglicher Lösungsansatz besteht darin, mittels Verfahren der Quellentrennung die beteiligten Instrumente vor der Analyse klanglich zu isolieren. Die Leistungsfähigkeit dieser Algorithmen ist zum aktuellen Stand der Technik jedoch nicht immer ausreichend, um eine sehr gute Trennung der Einzelquellen zu ermöglichen. In dieser Arbeit werden daher ausschließlich isolierte Instrumentalaufnahmen untersucht, die klanglich nicht von anderen Instrumenten überlagert sind. Exemplarisch werden anhand der elektrischen Bassgitarre auf die Klangerzeugung dieses Instrumentes hin spezialisierte Analyse- und Klangsynthesealgorithmen entwickelt und evaluiert.Im ersten Teil der vorliegenden Arbeit wird ein Algorithmus vorgestellt, der eine automatische Transkription von Bassgitarrenaufnahmen durchführt. Dabei wird das Audiosignal durch verschiedene Klangereignisse beschrieben, welche den gespielten Noten auf dem Instrument entsprechen. Neben den üblichen Notenparametern Anfang, Dauer, Lautstärke und Tonhöhe werden dabei auch instrumentenspezifische Parameter wie die verwendeten Spieltechniken sowie die Saiten- und Bundlage auf dem Instrument automatisch extrahiert. Evaluationsexperimente anhand zweier neu erstellter Audiodatensätze belegen, dass der vorgestellte Transkriptionsalgorithmus auf einem Datensatz von realistischen Bassgitarrenaufnahmen eine höhere Erkennungsgenauigkeit erreichen kann als drei existierende Algorithmen aus dem Stand der Technik. Die Schätzung der instrumentenspezifischen Parameter kann insbesondere für isolierte Einzelnoten mit einer hohen Güte durchgeführt werden.Im zweiten Teil der Arbeit wird untersucht, wie aus einer Notendarstellung typischer sich wieder- holender Basslinien auf das Musikgenre geschlossen werden kann. Dabei werden Audiomerkmale extrahiert, welche verschiedene tonale, rhythmische, und strukturelle Eigenschaften von Basslinien quantitativ beschreiben. Mit Hilfe eines neu erstellten Datensatzes von 520 typischen Basslinien aus 13 verschiedenen Musikgenres wurden drei verschiedene Ansätze für die automatische Genreklassifikation verglichen. Dabei zeigte sich, dass mit Hilfe eines regelbasierten Klassifikationsverfahrens nur Anhand der Analyse der Basslinie eines Musikstückes bereits eine mittlere Erkennungsrate von 64,8 % erreicht werden konnte.Die Re-synthese der originalen Bassspuren basierend auf den extrahierten Notenparametern wird im dritten Teil der Arbeit untersucht. Dabei wird ein neuer Audiosynthesealgorithmus vorgestellt, der basierend auf dem Prinzip des Physical Modeling verschiedene Aspekte der für die Bassgitarre charakteristische Klangerzeugung wie Saitenanregung, Dämpfung, Kollision zwischen Saite und Bund sowie dem Tonabnehmerverhalten nachbildet. Weiterhin wird ein parametrischerAudiokodierungsansatz diskutiert, der es erlaubt, Bassgitarrenspuren nur anhand der ermittel- ten notenweisen Parameter zu übertragen um sie auf Dekoderseite wieder zu resynthetisieren. Die Ergebnisse mehrerer Hötest belegen, dass der vorgeschlagene Synthesealgorithmus eine Re- Synthese von Bassgitarrenaufnahmen mit einer besseren Klangqualität ermöglicht als die Übertragung der Audiodaten mit existierenden Audiokodierungsverfahren, die auf sehr geringe Bitraten ein gestellt sind.Music recordings most often consist of multiple instrument signals, which overlap in time and frequency. In the field of Music Information Retrieval (MIR), existing algorithms for the automatic transcription and analysis of music recordings aim to extract semantic information from mixed audio signals. In the last years, it was frequently observed that the algorithm performance is limited due to the signal interference and the resulting loss of information. One common approach to solve this problem is to first apply source separation algorithms to isolate the present musical instrument signals before analyzing them individually. The performance of source separation algorithms strongly depends on the number of instruments as well as on the amount of spectral overlap.In this thesis, isolated instrumental tracks are analyzed in order to circumvent the challenges of source separation. Instead, the focus is on the development of instrument-centered signal processing algorithms for music transcription, musical analysis, as well as sound synthesis. The electric bass guitar is chosen as an example instrument. Its sound production principles are closely investigated and considered in the algorithmic design.In the first part of this thesis, an automatic music transcription algorithm for electric bass guitar recordings will be presented. The audio signal is interpreted as a sequence of sound events, which are described by various parameters. In addition to the conventionally used score-level parameters note onset, duration, loudness, and pitch, instrument-specific parameters such as the applied instrument playing techniques and the geometric position on the instrument fretboard will be extracted. Different evaluation experiments confirmed that the proposed transcription algorithm outperformed three state-of-the-art bass transcription algorithms for the transcription of realistic bass guitar recordings. The estimation of the instrument-level parameters works with high accuracy, in particular for isolated note samples.In the second part of the thesis, it will be investigated, whether the sole analysis of the bassline of a music piece allows to automatically classify its music genre. Different score-based audio features will be proposed that allow to quantify tonal, rhythmic, and structural properties of basslines. Based on a novel data set of 520 bassline transcriptions from 13 different music genres, three approaches for music genre classification were compared. A rule-based classification system could achieve a mean class accuracy of 64.8 % by only taking features into account that were extracted from the bassline of a music piece.The re-synthesis of a bass guitar recordings using the previously extracted note parameters will be studied in the third part of this thesis. Based on the physical modeling of string instruments, a novel sound synthesis algorithm tailored to the electric bass guitar will be presented. The algorithm mimics different aspects of the instrument’s sound production mechanism such as string excitement, string damping, string-fret collision, and the influence of the electro-magnetic pickup. Furthermore, a parametric audio coding approach will be discussed that allows to encode and transmit bass guitar tracks with a significantly smaller bit rate than conventional audio coding algorithms do. The results of different listening tests confirmed that a higher perceptual quality can be achieved if the original bass guitar recordings are encoded and re-synthesized using the proposed parametric audio codec instead of being encoded using conventional audio codecs at very low bit rate settings

The Mad Science of Hip-Hop: History, Technology, and Poetics of Hip-Hop\u27s Music, 1975-1991

In 1979, the first commercial recordings of hip-hop music were released. The music\u27s transition from the parks and clubs of the Bronx to recorded media resulted in hip-hop music being crafted and mediated in a recording studio before reaching the ears of listeners. In this dissertation I present a comprehensive investigation into the history of the instrumental component of hip-hop music heard on recordings, commonly referred to as beats. My historical narrative is formed by: the practices involved in the creation of hip-hop beats; the technologies that facilitated and defined those practices; and the debates around these two aspects that established the aesthetics of the music. The span of years covered in the dissertation are bookended by the establishment of precision breakbeat compositions on turntables in 1975 and the technological, economic, and legal developments in hip-hop music and culture that became a turning point for the practice of beat making and the sound of hip-hop music beginning in 1991. Beat makers, producers, and engineers--the recordists predominantly responsible for the sound of a hip-hop recording--are cultural producers involved in the social practice of cultural production. As such, the history in this study is informed by ethnographic research in the form of interviews and participant observation. Musical analyses are also utilized to illuminate the historical development of hip-hop music, particularly to display the ways that beat makers created their sound arrangements through the functions of certain technologies. This dissertation explores the intermingling of technology and human practice and serves as a foundation for further inquiry into the effect of technology on music making practices

Combining Metadata, Inferred Similarity of Content, and Human Interpretation for Managing and Listening to Music Collections

Music services, media players and managers provide support for content classification and access based on filtering metadata values, statistics of access and user ratings. This approach fails to capture characteristics of mood and personal history that are often the deciding factors when creating personal playlists and collections in music. This dissertation work presents MusicWiz, a music management environment that combines traditional metadata with spatial hypertext-based expression and automatically extracted characteristics of music to generate personalized associations among songs. MusicWiz’s similarity inference engine combines the personal expression in the workspace with assessments of similarity based on the artists, other metadata, lyrics and the audio signal to make suggestions and to generate playlists. An evaluation of MusicWiz with and without the workspace and suggestion capabilities showed significant differences for organizing and playlist creation tasks. The workspace features were more valuable for organizing tasks, while the suggestion features had more value for playlist creation activities

Creating music by listening

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (p. 127-139).Machines have the power and potential to make expressive music on their own. This thesis aims to computationally model the process of creating music using experience from listening to examples. Our unbiased signal-based solution models the life cycle of listening, composing, and performing, turning the machine into an active musician, instead of simply an instrument. We accomplish this through an analysis-synthesis technique by combined perceptual and structural modeling of the musical surface, which leads to a minimal data representation. We introduce a music cognition framework that results from the interaction of psychoacoustically grounded causal listening, a time-lag embedded feature representation, and perceptual similarity clustering. Our bottom-up analysis intends to be generic and uniform by recursively revealing metrical hierarchies and structures of pitch, rhythm, and timbre. Training is suggested for top-down un-biased supervision, and is demonstrated with the prediction of downbeat. This musical intelligence enables a range of original manipulations including song alignment, music restoration, cross-synthesis or song morphing, and ultimately the synthesis of original pieces.by Tristan Jehan.Ph.D

"The Revolution Will Not Be Televised...But It Will Be Streamed": Spotify, Playlist Curation, and Social Justice Movements

Since its launch in 2008, the Swedish-based audio streaming service Spotify has transformed how consumers experience music. During the same time, Spotify collaborated with social justice activists as a means of philanthropy and brand management. Focusing on two playlists intended to promote the Black Lives Matter movement (2013–) and support protests against the U.S. “Muslim Ban” (2017–2020), this thesis explores how Spotify’s curators and artists navigate the tensions between activism and capitalism as they advocate for social justice. Drawing upon Ramón Grosfoguel’s concept of subversive complicity (2003), I show how artists and curators help promote Spotify’s progressive image and bottom line while utilizing the company’s massive platform to draw attention to the people and causes they care most about by amplifying their messages.Master of Art

Listening Context and Listening Mode: Towards a Unified Approach for Examining the Connection between Music, Emotion, and Mood.

A comprehensive investigation into music and emotion/mood research models (Eerola & Vuoskoski, 2013)1 uncovered notable shortfalls in the selection of test instruments (primacy of classical recordings); limitations of testing conditions (clinical, theoretical, or self-reporting); opportunistic choice of test participants (selected out of convenience); and research practice following historical models (scientific or sociological methodologies). This paper sought to address these issues and presented a considered approach to sourcing music stimuli; identified a wider participant cross-section and testing options; and pinpointed the need for the application of a unified, interdisciplinary research method - a model that can integrate music’s disciplines, forms, and types of engagement (ie. systematic musicology)2 with a human’s neural, physiological, behavioural, and expressive elements (ie. psychophysiology):(Systematic) Musicology today covers all disciplinary approaches to the study of all music in all its manifestations and all its contexts, whether they be physical, acoustic, digital, multimedia, social, sociological, cultural, historical, geographical, ethnological, psychological, physiological, medicinal, pedagogical, therapeutic, or in relation to any other musically relevant discipline or context. (Parncutt, 2007. Ibid.).Scientific methodologies (biological/neurological) measure physiological responses at the expense of psychoacoustic responses - an assumption that clinical measurement techniques andalgorithmic solutions present an efficient model to classify or explain the relationship between music and emotion/mood. Sociological methodologies (psychological/theoretical) suppose thatsymbolic interactionism or structural functionalism in music drives an emotional response and affects mood - an assumption that music is a semiotic system, and its constructs are either reflections of the cultural genre around which that music grew or inherent personality traits - and are imbued with messages and meaning. Therefore, this paper proposed a mixed method analysis to measure the true effect of music manifestations on emotion/mood.Outlined in this document are four aspects central to performing a critical investigation into music vs emotion/mood: a) the need for clear principles and criteria in the curation of test instruments and test subjects, b) the importance of the listening context (profile, orientation, and acrophase) of respondents, c) the significance of the listening mode (cause-based, semantic-focus, or ambient-type) of respondents in the research process, and d) the recognitionof music-induced emotions and their physiological/psychological triggers on respondents is temporal, as music means different things to different people at different times.This paper annotated key musical stimuli (music elements/genres), examined listening contexts (situational macro-variables), and explored listening modes (cognition/appreciation factors) that impact upon listening experiences using a 5W+1Hi inquiry method for compilation. Selected historical cases of claimed music-induced emotional responses or behavioural modification, as well as consciously constructed works by composers to elicit emotionalresponses, were presented side-by-side with theoretical templates used to map emotion/mood.As music-listening experiences today integrate a substantial visual/interactive component in their consumption, via a proliferation of audio-visual device options (screen music, musicvideo, promotional/commercial contents), a diverse range of samples were also included in the paper’s discussion. The general recommendations and conclusions of this paper were that:i) in the development-stage of the music/emotion/mood research plan, it is paramount that a curated menu of test instruments, applicable across a representative spectrum of listeners, and measurable in varying listening environments, be created prior to undertaking research.ii) using test instruments without a qualifying listening context template, and using test procedures without distinguishing listening mode foci, will diminish research results. Participant-profiling will determine listening backgrounds/purposes and fine-tune testing.iii) via the lens of systematic musicology which encompasses all music disciplines, and an integrated quantitative/qualitative data collection and analysis or mixed method research model (Creswell & Plano Clark, 2011)3, this will address shortcomings of prior research.1 Eerola, T., and Vuoskoski, J. (2013, February). A Review of Music and Emotion Studies: Approaches, Emotion Models, and Stimuli. In Music Perception. An interdisciplinary Journal. Volume 30. Issue 3. pp. 307-340.2 Parncutt, R. (2007, Spring). Systematic musicology and the history and future of western musical scholarship. In Journal of Interdisciplinary Music Studies. Volume 1, Issue 1, pp. 1-32.3 Creswell, J. and Plano Clark, V. (2011). Designing and conducting mixed methods research. Sage

Analyzing Genre in Post-Millennial Popular Music

This dissertation approaches the broad concept of musical classification by asking a simple if ill-defined question: “what is genre in post-millennial popular music?” Alternatively covert or conspicuous, the issue of genre infects music, writings, and discussions of many stripes, and has become especially relevant with the rise of ubiquitous access to a huge range of musics since the fin du millénaire. The dissertation explores not just popular music made after 2000, but popular music as experienced and structured in the new millennium, including aspects from a wide chronological span of styles within popular music. Specifically, with the increase of digital media and the concomitant shifts in popular music creation, distribution, and access, popular music categorization has entered a novel space, with technologies like internet radio, streaming services, digital audio workstations, and algorithmic recommendations providing a new conception of how musical types might be understood and experienced. I attempt to conceptualize this novel space of genre with what I call a genre-thinking or a genreme, a term which is meant to capture the ways that musical categorization infiltrates writings about, experiences of, and the structures connecting genres. This dissertation comprises four main chapters, each of which takes a slightly different perspective and approach towards questions concerning genre in popular music of the post-millennial era. Chapter 1 provides a general survey and summary of music theory’s and musicology’s discourses on musical categorization and genre. After describing the “problem of genre,” I outline the main issues at stake and chief strategies previous authors have employed. This involves describing the closely intertwined facets of the “who” of genre (is a musical category defined by music, a musician, an audience, the industry?) and the “how” of genre (is it a contract, a definition, a pattern, a system, an experience?) By asking these questions, I open new approaches to understanding and analyzing genre’s role in both the structure and potential experiences of post-millennial popular music. Chapter 2 takes on the digital compositional practice of mashups—most prevalent in the first decade of the 2000s—in an attempt to understand genre as a crucial element of meaning-formation and creation. Previous mashup scholars have tended to focus on the ironic, subversive, or humorous juxtapositions of the particular samples or artists which get layered together. However, this leaves out the broad, exceptionally potent acts of signification that are possible even when a listener lacks the knowledge of the specific autosonic source materials. By incorporating methodologies from musical semiotics and topic theory, I create a field of “interaction methods” to explain the dynamic relations between samples, exploding the analytical potential for signification and collaboration in mashups. These interaction methods are placed in dialogue with formal analysis to show ways that artists, samples, and genres intermingle in this form of digital musicking. Chapters 3 and 4 then progress chronologically into the second decade of the new millennium, taking a twinned approach to our contemporary world of streaming services and online musical cultures. First, I pursue a brief musicological and sociological exploration of current discourses engaged with genre in the 2010s, outlining the ways that critics, fans, and musicians deploy stylistic terms and musical categories. A somewhat paradoxical position emerges in which genre is both in a state of decline and a state of proliferation, simultaneously atrophying yet employed in increasingly abundant and sophisticated manners. I then describe how this contradictory state fits into sociological research on “omnivorousness” and musical taste. The following chapter investigates how these perceptions and linguistic usages of genre compare to two main ways that Spotify classifies its artists. This quantitative analysis reveals some potential systemic patterns of bias that shed light onto genre’s paradoxical position; whether genre is dead or not depends on who is classifying the music and who is being classified. These two chapters map out my concept “#genre” which I employ to describe the multivalent genre-thinking we currently inhabit

Expressive musical process: exploring contemporary jazz musicians' views on the use of expressivity in compositional practice

Although there is a wide range of literature exploring expressivity in contemporary jazz music, I have found little to address the way that jazz musicians apply their expressivity in acts of composition. Moreover, I have found little academic research into the way that jazz musicians conceptualise their own expressivity in relation to their practice. This thesis uses this as an opportunity to interrogate the notion of ‘expressivity’ as a motivation for new compositional practice. I harness this concept explicitly in my own practical work, in order to illustrate how expressivity can be deliberately exploited within jazz composition. This investigation addresses the following questions: How does expressivity impact communication between jazz players? How do jazz musicians understand the relationship between expressivity and improvisation? How do composers of contemporary jazz talk about expressivity in relation to instrumentation? How do contemporary jazz musicians discuss the use of expressivity in modal composition? The methodology of this research can be broken down as two different strands of investigation. First, I interviewed a number of contemporary jazz musicians about the notion of musician’s expressivity, and how they embody this concept in their own practice. Secondly, I have composed new jazz music that responds to these themes and practically illustrates the concepts that I discuss. Throughout this analytical and practical process, I discuss expressivity in relation to four core concepts which are engaged with throughout this text: communication, improvisation, instrumentation and modal composition. Each of these themes is used to unpick, define and explore the concept of expressivity from different perspectives. Underpinning this high-level conceptual framework, around sixty lowlevel theoretical themes have finally shaped the musical trajectory of this project. Seven original compositions of new work support this written thesis, featuring two hours of musical experimentation. This sonic component is used to evidence key claims made in my thesis. Overall, my analysis leads me to conclude that expressivity allows us to see contemporary jazz from a very human-sensitive perspective. Expressivity encourages us to study the complex range of distinctive musical, cultural, technical and social factors that intersect when jazz musicians meet in performance. The unique expressive aptitudes of these various relational qualities can be channelled in the design of original musical works which treat expressivity as a mobilising factor for musical composition