NLP for Music and Audio Workshop Announcement repost


We would like to invite you to send your contributions to NLP4MusA, the first Workshop on Natural Language Processing for Music and Audio, co-located with ISMIR 2020. 



When: October, 16

Where: ISMIR 2020 (Montreal)

Submission deadline: July, 17

Proceedings: Accepted papers will be published on the ACL Anthology.

Sponsors: Pandora, Deezer and Spotify



Natural Language Processing (NLP) research is typically associated with the advancement of language technologies. However, in today’s growing digital landscape, where users engage with other users, products and service providers, NLP is becoming ubiquitous due to its ability to facilitate and personalize access to digital content of any nature. One case of particular relevance is the audio entertainment industry, as language is a key component of most audio content (e.g., songs, podcasts, radio shows, audio ads, etc.) as well as user-content interactions (e.g., textual queries, spoken utterances, social media activity, etc.). 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. 


Topics of Interest

We welcome both academic and industry submissions at the crossroads of NLP and music and audio, including (but not limited to) topics such as:


  • NLP for Music and Audio Understanding
    • Tagging and meta-tagging
    • Knowledge graph construction
    • Information extraction
    • Named entity recognition and linking
    • Speech to text
    • Song and podcast segmentation
    • Topic modeling
    • Sentiment analysis
    • Representation learning
    • Bias in music and audio corpora
    • Audio captioning
    • Debiasing music entity embeddings


  • NLP for Music and Audio Retrieval and Personalization
    • Conversational AI
    • Slot filling and intent prediction
    • Information retrieval
    • Cross-modal retrieval
    • Recommender systems
    • Ads personalization
    • Responsible recommendations
    • Fairness and transparency


  • NLP for Music and Audio Generation
    • Lyrics generation
    • Music generation with language models
    • Spoken audio/podcast generation


Keynote Speakers:

Colin Raffel, Google Brain

Sam Mehr, Harvard University


Submission Instructions

We invite extended abstracts of up to 2 pages or short-papers of up to 4 pages (excluding references). The review process will be double-blind. Submissions should adhere to the ACL Anthology formatting guidelines. 


A LaTeX template is available here:


Only papers using the above template will be considered. Word templates will not be provided.


Papers should be submitted via EasyChair:


Important dates vb 

Submission Deadline: July 17, 2020

Notification of Acceptance: August 7, 2020

Camera-Ready Deadline: September 4, 2020

Workshop Date: October 16, 2020


Organizing Committee

  • Sergio Oramas, Pandora (soramas [at] pandora [dot] com)
  • Massimo Quadrana, Pandora (mquadrana [at] pandora [dot] com)
  • Luis Espinosa-Anke, Cardiff University
  • Elena Epure, Deezer
  • Rosie Jones, Spotify
  • Mohamed Sordo, Pandora
  • Kento Watanabe, AIST


Program Committee

  • Marion Baranes (Deezer)
  • Francesco Barbieri (Snap)
  • Elena Cabrio (Université Cote d’Azur)
  • José Camacho-Collados (Cardiff University)
  • Iñigo Casanueva (Poly AI)
  • Christos Christodoulopoulos (Amazon)
  • Ann Clifton (Spotify)
  • Albin Correya (UPF)
  • Andrés Ferraro (UPF)
  • George Fazekas (QMUL)
  • Michael Fell (Université Cote d’Azur)
  • Gregory Finley (Pandora)
  • Ichiro Fujinaga (McGill University)
  • Masataka Goto (AIST)
  • Fabien Gouyon (Pandora)
  • Romain Hennequin (Deezer)
  • Peter Knees (TU Wien)
  • Mark Levy (Apple)
  • Pasquale Lisena (EURECOM)
  • Manuel Moussallam (Deezer)
  • Aasish Pappu (Spotify)
  • Lorenzo Porcaro (UPF)
  • Zahra Rahimi (Pandora)
  • Sravana Reddy (Spotify)
  • Giuseppe Rizzo (LINKS Foundation)
  • Horacio Saggion (UPF)
  • Markus Schedl (TU Linz)
  • Richard Sutcliffe (University of Essex)
  • Scott Waterman (Pandora)
  • Minz Won (UPF)
  • Shuo Zhang (BOSE Corporation)

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