A Summarization for Labs and People in Music Technology (Useful Links Attached!)

(2020) I was trying to summarize labs and researchers around the world who dedicate in music computation. I was writing this list because I really wanted to do researches about MIR and music generation. Of course, this list is far from complete, and will be out-of-date in a few years. If you have recommendations, feel free to comment below!

If You Did not Know about MIR

Here is a superfacial introduction for starters and for people who are interested in music computation.

MIR means Music Information Retrieval. Its relevant topics are broad! If I am talking about MIR, I am refering to the topics which trie to analyze everything about music in a technological fashion. In many cases, MIR is a term which has the same meaning with “music computation”. By the way, another term “music technology” mainly means topics about synthesizers, digital music formats (e.g. MIDI, mp3) and instruments, which emphasizes differently from the term “MIR”.

You may be curious about how to identify a song by humming, which is an MIR topic called Query by Humming (wiki). You may also be curious about how to translate a musical performance into scores, which is an MIR topic called automatic music transcription (AMT) (paper). Other interesting topics include music recommendation (blog), computational musicology (blog), sound synthesizing (blog) and algorithm composing (wiki) etc., which are all relevant topics.
Search “MIR” in wiki: https://en.wikipedia.org/wiki/Music_information_retrieval.

Those listed above are all tasks/goals. But what about the methodology to achieve them? Remember: music is created by people. Therefore, tasks about understanding musical rules and phenomenons are actually tasks about understanding human thoughts. How to understand them?
Well… On the one hand, the nature of music is audio and the nature of musical understandings is human cognition; thus, we have to deal with audio properties and human perceptions. Relevant techonologies include Digital Signal Processing (wiki), Synthesizer (wiki) and Cognitive Musicology (paper).
On the other hand, music is a kind of rule-based art, and we are interested in such rules. But how to understand and apply such rules? Relevant methods include Music as Language (paper), Natural Language Processing (NLP)(wiki). We know that the “rules” in rule-based-arts are far from simple. Therefore, we have to use systems which have great complexity to fit to those rules. Such method is machine learning (paper).
With such tools, we can deal with problems which are directly relevant to music. For example, we can design our “generative music language”, and then apply it for algorithm composing. Or we can apply the DSP methods to identify chords from audio. Of course, every topic has its unique side. Therefore, never stop learning!

The following links in the rest of this page are all relevant with what I introduced before.

Labs, Groups and Individual Researchers

  • Archives, Journals and Societies about “Science & Music” by University of Cambridge, Center for Music and Science:
    https://cms.mus.cam.ac.uk/links
    This page is a summarization of research groups and research society mainly in Europe. You may find links of research groups as well as academic sources in this page.
  • Research Centers Summarized by Beici Liang:
    https://mp.weixin.qq.com/s/2nDWikda9fh2x5o093F6HA
    The groups mentioned in this list are mostly in universities. By the way, the wechat official account (in Chinese 中文) in this link is a tutorial for beginners who are interested in music tech.

I give those comprehensive links first. After all, I have to reinvent the wheel because I cannot remember all of them unless I write them down and read them all.

My summarization

Here is a summarization of research group websites I have visited. My list is far from complete. I am just writing them down in order to have a review on the MIR society I have explored, straightening my mind. After all, I felt dizzy when I first began to search about MIR groups around the world…
If you are a starter, hope that the following links can help you. If you are already a researcher, well… hope that my naive list does not bother you and that you can give some suggestions!
Note that the information here is limited. I may have left out or misunderstood a lot of information. Therefore, the information in my list is inevitably biased! Again, this list is created mainly for myself and for starters to get familiar with the MIR society. If I wrote something improper, please contact me for correction!

…To be expanded

Europe

Asia

America

  • Center for Computer Research in Music and Acoustics (CCRMA), Stanford University
    https://ccrma.stanford.edu/
    This is a big lab. There are many groups in CCRMA. See here.
  • Prof. Roger B. Dannenberg, CMU
    http://www.cs.cmu.edu/~rbd/
    A great computer music research, a camposer and a trumpet player. However, he is not accepting students.
  • Centre For Interdisciplinary Research in Music Media And Technology (CIRMMT), McGill University
    https://www.cirmmt.org/
    A big lab.

Research Groups in Industry

…Pending

An outline: Google Magenta, Spotify, Open AI, NAVIDA, Jukedeck - TikTok London, Tencent Music (TME), Netease Music…

Useful Links

Pages of Conferences

  • ISMIR (International Society for Music Information Retrieval)
    https://ismir.net/
    “The ISMIR conference is held annually and is the world’s leading research forum on processing, searching, organising and accessing music-related data.”
  • MIREX (Music Information Retrieval Evaluation eXchange)
    https://www.music-ir.org/mirex/wiki/MIREX_HOME
    “The Music Information Retrieval Evaluation eXchange (MIREX) is an annual evaluation campaign for MIR algorithms, coupled to the ISMIR conference.”
  • SMC (Sound and Music Computing Network)
    http://www.smcnetwork.org/
    “The SMC Conference is a double-blind peer-reviewed international scientific conference around the core interdisciplinary topics of Sound and Music Computing.”
  • NLP4MusA
    https://sites.google.com/view/nlp4musa
    “In this context, we propose the First Workshop on NLP for Music and Audio, a forum for bringing together academic and industrial scientists and stakeholders interested in exploring synergies between NLP and music and audio.” “Accepted papers will be published in the ACL anthology.”
  • CSMT (Conference on Sound and Music Techonology)
    http://www.csmcw-csmt.cn/
    CSMT是中国音乐科技相关的研究者交流的很好平台，可以见到很多工业界和学术界的同行。CSMT推动者中国的音乐科技领域的发展合作，也在吸引世界范围内学术界的关注。

Of course, information here is limited due to my limited knowledge… More links pending…

Dataset sources

  • Datasets summarized by Prof. Alexander Lerch, Gatech
    https://www.audiocontentanalysis.org/data-sets/
    A grrrrrreat list of useful music datasets. Brief tags are attached there (e.g. MIDI or not? Labelled or not? Rhythm or melody? Monophonic or Polyphonic…)

Blogs

  • …To be expanded
  • And… Hey! And my blog here!
  • dblp: computer science bibliography
    https://dblp.uni-trier.de/
    “The dblp computer science bibliography provides open bibliographic information on major computer science journals and proceedings.”
  • Papers With Code: The latest in machine learning
    https://paperswithcode.com/
    “Papers With Code highlights trending ML research and the code to implement it.”
  • imslp: download sheet music
    https://imslp.org/wiki/Main_Page
    “The International Music Score Library Project (IMSLP), also known as the Petrucci Music Library after publisher Ottaviano Petrucci, is a subscription-based project for the creation of a virtual library of public-domain music scores.” - wiki
  • Google scholar, Media, Wiki, Zhihu, CSDN…
本文作者： lucainiaoge
本文链接： https://lucainiaoge.github.io.git/2020/08/02/music-computation-labs-and-people-and-useful-links/
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