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An Introduction
MIR is a considerably new research area that addresses the question of finding and retrieving music documents, such as audio files, MIDI files, and sheet music. Even though the concept of MIR literally accommodates both meta data and content-based retrieval methods, it has been widely used as a synonym for content-based music information retrieval. In MIR the documents are searched and browsed using musical parameters as keys. Depending on the application, you may search for a song by humming its melody to a microphone connected to your retrieval system or browse a music collection using the similarity of sound, that is instrumentation and tempo, as your similarity measure.
Background for this growth
Music is a widely enjoyed content type, existing in many multifaceted representations. With the digital information age, a lot of digitized music information has theoretically become available at the user’s fingertips. However, the abundance of information is too large-scaled and too diverse to annotate, oversee and present in a consistent and human manner, motivating the development of automated Music Information Retrieval (Music-IR) techniques.
MIR methods
The MIR methods can be divided into two main categories: audio and symbolic methods. The audio retrieval uses mainly digital signal processing methods and addresses the problem of finding music based on its audio content. The common subtasks for audio retrieval methods are, for instance, beat and tempo tracking, frequency estimation and classification based on these features.
The symbolic MIR is based on the score instead of audio. In symbolic presentations, music is presented as sets or sequences of symbols, each of them describing a musical event, most often a note. The most widely known application of symbolic MIR is the so-called query-by-humming retrieval method in which the music is retrieved by humming a small fragment of melody, which is then converted into symbolic form for the actual retrieval task. Thus, symbolic MIR is highly based on the similarity of the score.
Domain
MIR is a highly-interdisciplinary field bridging the domains of digital audio signal processing, pattern recognition, software system design, and machine learning. Simply put, MIR algorithms allow a computer to "listen" and "understand or make sense of" audio data, such as MP3s in a personal music collection, live streaming audio, or gigabytes of sound effects, in an effort to reduce the semantic gap between high-level musical information and low-level audio data. In the same way that listeners can recognize the characteristics of sound and music - tempo, key, chord progressions, genre, or song structure - MIR algorithms are capable of recognizing and extracting this information, enabling systems to perform extensive sorting, searching, music recommendation, meta data generation, transcription, and even aiding/generating real-time performance.
Scope
Music Information Retrieval (MIR) i involves researchers, developers, educators, librarians, students and professionals from the disciplines of musicology, cognitive science, library and information science, computer science, electrical engineering and many others.
MIR Industry (a few examples)
Recommendation, Playlisting: Pandora Spotify. YouTube Music
Amazon Prime Music Heart
Audio Identification: Shazam Gracenote
Score Following: Rock Prodigy SmartMusic Rockband
Others: Bose LANDR Smule Native Instruments ROLI Steinberg
For examples of a vibrant community: Monthly Music Hackaton
Bridging industry and academia: Real industry
Music Information Retrieval Conferences
International Conference on Acoustics, Speech, and Signal Processing
(ICASSP)
International Computer Music Association
Sound and Music Computing (SMC)
Neural Information Processing Systems (NIPS)
The International Society for Music Information Retrieval conference (ISMIR)
(ISMIR) The International Society for Music Information Retrieval conference
introduction
The International Society for Music Information Retrieval (ISMIR) is a non-profit organization which, among other things, oversees the organization of the ISMIR Conference. The ISMIR conference is held annually and is the world's leading research forum on processing, searching, organizing and accessing music-related data. Music becomes music after being processed by the human mind and each person perceives the music in a different and complex way. Therefore, this conference embraces the complexity and diversity of music by showcasing ideas and applications that aim to enhance the way in which we interact with music.
ISMIR conference provides a venue for the exchange of ideas, issues, results and perspectives among the different profiles of people working with music and computing in a broad sense. The Society reports recent activities at the yearly ISMIR Community Meeting (held during the Conference).
Submissions are accepted for:
Conference Papers
Tutorials
Late-breaking Papers & Demos
Exhibition of Installation using Interactive Machine-Learning for Music
Topics of Interest include but are not limited to:
MIR data and fundamentals
music signal processing
symbolic music processing
meta data, tags, linked data, and semantic web
lyrics and other textual data, web mining, and natural language processing
multi modality
Domain knowledge:
representations of music
music acoustics
computational music theory and musicology
cognitive MIR
machine learning/artificial intelligence for music
corpus creation
annotation methodology
evaluation methodology
legal issues
Each year, the ISMIR conference is held in a different corner of the world to motivate the presentation and exchange of ideas and innovations related to the intentionally broad topic of music information. Historically, the call for papers (CFP) is announced in the beginning of the year (February-May) via the community mailing list, and conferences are held several months later (August-November).
With the exception of the scientific proceedings, the format of the conference varies slightly from year to year; the local organizers are encouraged to leave their unique mark on the conference, and the greater society is continually experimenting and improving upon the event.
Upcoming Conference
ISMIR 2019, Delft (The Netherlands)
Funding is secured for successful students in order to travel to the annual ISMIR conference to present their results.
The Music Information Retrieval Evaluation eXchange (MIREX)
The Music Information Retrieval Evaluation eXchange (MIREX) is an annual community-based framework for the formal evaluation of Music Information Retrieval (MIR) systems and algorithms. coupled to the ISMIR conference .MIREX tasks are defined by the community they reflect the interests, techniques, and research paradigms of the community as a whole. Since it started in 2005, MIREX has fostered advancements both in specific areas of MIR and in the general understanding of how MIR systems and algorithms are to be evaluated. MIREX is to the MIR community what the Text Retrieval Conference (TREC) is to the text information retrieval community:
MIREX, however, does differ from TREC in one very important aspect. Unlike TREC, the datasets used in the MIREX evaluation process are not distributed freely among the participants A set of community-defined formal evaluations through which a wide variety of state-of-the-art systems, algorithms and techniques are evaluated under controlled conditions. MIREX is managed by the International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) at the University of Illinois at Urbana-Champaign (UIUC)
IMIRSEL personnel are responsible for gathering (from various sources) and managing huge collections of music and ground-truth data (in a wide variety of formats). Responsibilities also include verifying the integrity of the test data itself and securing the data sets from malicious downloading. IMIRSEL is also responsible for managing the massive amounts of intermediate data that are created during the evaluation process, usually in the form of very large feature sets and similarity matrices that are common to many audio-based techniques.
MIREX Competition
The MIREX competition (Music Information Retrieval Evaluation eXchange) is an annual competition targeting challenging machine learning tasks related to music. You may choose one of the MIREX challenges as your Master's thesis project.
Some example projects are:
For a complete list of challenges to choose from, you may visit the MIREX home page.
Suggested qualifications:
Machine learning / Deep learning (e.g. INF5860, INF4490),Sound Analysis (MUS4831), Methods course in Cognitive Musicology (MUS4218)
