Audio Content-Based Music Retrieval

The rapidly growing corpus of digital audio material requires novel retrieval strategies for exploring large music collections. Traditional retrieval strategies rely on metadata that describe the actual audio content in words. In the case that such textual descriptions are not available, one requires content-based retrieval strategies which only utilize the raw audio material. In this contribution, we discuss content-based retrieval strategies that follow the query-by-example paradigm: given an audio query, the task is to retrieve all documents that are somehow similar or related to the query from a music collection. Such strategies can be loosely classified according to their "specificity", which refers to the degree of similarity between the query and the database documents. Here, high specificity refers to a strict notion of similarity, whereas low specificity to a rather vague one. Furthermore, we introduce a second classification principle based on "granularity", where one distinguishes between fragment-level and document-level retrieval. Using a classification scheme based on specificity and granularity, we identify various classes of retrieval scenarios, which comprise "audio identification", "audio matching", and "version identification". For these three important classes, we give an overview of representative state-of-the-art approaches, which also illustrate the sometimes subtle but crucial differences between the retrieval scenarios. Finally, we give an outlook on a user-oriented retrieval system, which combines the various retrieval strategies in a unified framework

Music 2025 : The Music Data Dilemma: issues facing the music industry in improving data management

© Crown Copyright 2019Music 2025ʼ investigates the infrastructure issues around the management of digital data in an increasingly stream driven industry. The findings are the culmination of over 50 interviews with high profile music industry representatives across the sector and reflects key issues as well as areas of consensus and contrasting views. The findings reveal whilst there are great examples of data initiatives across the value chain, there are opportunities to improve efficiency and interoperability

Signal processing methods for beat tracking, music segmentation, and audio retrieval

The goal of music information retrieval (MIR) is to develop novel strategies and techniques for organizing, exploring, accessing, and understanding music data in an efficient manner. The conversion of waveform-based audio data into semantically meaningful feature representations by the use of digital signal processing techniques is at the center of MIR and constitutes a difficult field of research because of the complexity and diversity of music signals. In this thesis, we introduce novel signal processing methods that allow for extracting musically meaningful information from audio signals. As main strategy, we exploit musical knowledge about the signals\u27 properties to derive feature representations that show a significant degree of robustness against musical variations but still exhibit a high musical expressiveness. We apply this general strategy to three different areas of MIR: Firstly, we introduce novel techniques for extracting tempo and beat information, where we particularly consider challenging music with changing tempo and soft note onsets. Secondly, we present novel algorithms for the automated segmentation and analysis of folk song field recordings, where one has to cope with significant fluctuations in intonation and tempo as well as recording artifacts. Thirdly, we explore a cross-version approach to content-based music retrieval based on the query-by-example paradigm. In all three areas, we focus on application scenarios where strong musical variations make the extraction of musically meaningful information a challenging task.Ziel der automatisierten Musikverarbeitung ist die Entwicklung neuer Strategien und Techniken zur effizienten Organisation großer Musiksammlungen. Ein Schwerpunkt liegt in der Anwendung von Methoden der digitalen Signalverarbeitung zur Umwandlung von Audiosignalen in musikalisch aussagekräftige Merkmalsdarstellungen. Große Herausforderungen bei dieser Aufgabe ergeben sich aus der Komplexität und Vielschichtigkeit der Musiksignale. In dieser Arbeit werden neuartige Methoden vorgestellt, mit deren Hilfe musikalisch interpretierbare Information aus Musiksignalen extrahiert werden kann. Hierbei besteht eine grundlegende Strategie in der konsequenten Ausnutzung musikalischen Vorwissens, um Merkmalsdarstellungen abzuleiten die zum einen ein hohes Maß an Robustheit gegenüber musikalischen Variationen und zum anderen eine hohe musikalische Ausdruckskraft besitzen. Dieses Prinzip wenden wir auf drei verschieden Aufgabenstellungen an: Erstens stellen wir neuartige Ansätze zur Extraktion von Tempo- und Beat-Information aus Audiosignalen vor, die insbesondere auf anspruchsvolle Szenarien mit wechselnden Tempo und weichen Notenanfängen angewendet werden. Zweitens tragen wir mit neuartigen Algorithmen zur Segmentierung und Analyse von Feldaufnahmen von Volksliedern unter Vorliegen großer Intonationsschwankungen bei. Drittens entwickeln wir effiziente Verfahren zur inhaltsbasierten Suche in großen Datenbeständen mit dem Ziel, verschiedene Interpretationen eines Musikstückes zu detektieren. In allen betrachteten Szenarien richten wir unser Augenmerk insbesondere auf die Fälle in denen auf Grund erheblicher musikalischer Variationen die Extraktion musikalisch aussagekräftiger Informationen eine große Herausforderung darstellt

Looking Into the Meaning of Vaporwave: The Internet’s Favorite Genre of Music

Senior Project submitted to The Division of Arts of Bard College. An Ethnographic look into Vaporwave as a genre, and the politics surrounding it and it\u27s online community

Automatic transcription of traditional Turkish art music recordings: A computational ethnomusicology appraoach

Thesis (Doctoral)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2012Includes bibliographical references (leaves: 96-109)Text in English; Abstract: Turkish and Englishxi, 131 leavesMusic Information Retrieval (MIR) is a recent research field, as an outcome of the revolutionary change in the distribution of, and access to the music recordings. Although MIR research already covers a wide range of applications, MIR methods are primarily developed for western music. Since the most important dimensions of music are fundamentally different in western and non-western musics, developing MIR methods for non-western musics is a challenging task. On the other hand, the discipline of ethnomusicology supplies some useful insights for the computational studies on nonwestern musics. Therefore, this thesis overcomes this challenging task within the framework of computational ethnomusicology, a new emerging interdisciplinary research domain. As a result, the main contribution of this study is the development of an automatic transcription system for traditional Turkish art music (Turkish music) for the first time in the literature. In order to develop such system for Turkish music, several subjects are also studied for the first time in the literature which constitute other contributions of the thesis: Automatic music transcription problem is considered from the perspective of ethnomusicology, an automatic makam recognition system is developed and the scale theory of Turkish music is evaluated computationally for nine makamlar in order to understand whether it can be used for makam detection. Furthermore, there is a wide geographical region such as Middle-East, North Africa and Asia sharing similarities with Turkish music. Therefore our study would also provide more relevant techniques and methods than the MIR literature for the study of these non-western musics

The Utility of Resistance in Environments for Live Performance with Electronics as Part of a Compositional Strategy

The portfolio of compositions and accompanying commentary presented here deal with three key themes: resistance, liveness, and studioness. In the introduction, resistance is split into two forms: aesthetic and practical. Aesthetic resistance is established as a productively disruptive relationship with a perceived set of musical conventions, building on theoretical work by Kohn (1997), Hegarty (2008) and Thompson (2017). Practical resistance is identified in the relationship between performers and their performance environments, inspired by Noise performance practice and Ferguson’s (2013) writing on the subject, where performers perceive unpredictability and instability in their performance environments as resistant to their authorial control. Following Phelan (2005) and Auslander (2012), liveness is found in real-time public renderings of music where performers look to take advantage of the unique affordances of their live performance situation. Studioness is identified in situations where performers make use of the unique affordances of the studio to make work where the studio’s presence is clearly evident.The portfolio of compositions (comprising two projects: ‘Spectra’ and ‘Slow Loris’) seeks to investigate the relationship between live performance and studio practice in Experimental Electronica. It employs the idea of resistance to help cultivate a condition of liveness within this context. This live practice is then examined in the studio, asking how the resistant qualities of the live material might be expressed in the studio practice? Can these artefacts of resistance be translated into something with an idiomatic studioness? The possibilities of this approach are the focus of both music and commentary. The commentary also deals with resistance in historical and contemporary theorisations of improvisation and live performance with electronics, and expressions of liveness and studioness in Noise and Experimental Electronica, reflecting upon the effectiveness of the author’s compositional methodology and the ongoing relationship between his live practice and studio work

Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

Mechanized Metrics: From Verse Science to Laboratory Prosody, 1880-1918

Post-print version of the article deposited in accordance with SHERPA RoMEO guidelines. Copyright © 2009, Johns Hopkins University Press. This article first appeared in Configurations: A Journal of Literature, Science and Technology Vol.17(3), pp285-308. Reprinted with permission by The Johns Hopkins University Press.From roughly the 1880s, a methodical verse “science” was beginning to assert itself. Gripped by the thought of articulating an objective, fact-based metrics, poetry scientists brought to bear on the traditional verse line principles of observation and later full-blown experimental practices--not to mention a curious array of instrumentation. By the turn of the century, metrical verse was being subjected to a rigorous measurement regime, which employed techniques and apparatus derived from the new disciplines of experimental physiology and psychology. Proponents of this newly mechanized metrics pitched themselves enthusiastically into the turn-of-the-century prosody fray, believing they could resolve, once and for all, some of the fundamental dilemmas of versification

Communicating Air: Alternative Pathways to Environmental Knowing through Computational Ecomedia

This dissertation, Communicating Air: Alternative Pathways to Environmental Knowing through Computational Ecomedia, is the culmination of an art practice-led investigation into ways in which the production of ecomedia may open alternative pathways to environmental knowing in a time of urgent climate crisis. This thesis traces the author’s artistic, personal and political development across the period of study and presents an extended argument for greater public engagement with weather and climate science, greater public and private support for long-term collaborations between media art and climate science, and increased public open access to global weather and climate monitoring and computationally modelled data