NLP4MusA

First Workshop on NLP for Music and Audio

October 16, 2020 | Montreal

co-located with ISMIR'2020

Check the CFP of the 2021 edition

>>> Check the Proceedings here <<<

The workshop will be held on October 16th and 17th 2020. All presentations will be live on the 16th and streamed on the 17th. Posters Q&A sessions will be live on both days.

Make sure to check out the list of Invited Speakers and the Program of the workshop.

Check out the videos of the Workshop in our YouTube channel

Time-Zone Friendly Schedule

Agenda (October 16th, UTC-4):

Opening + Keynote 1 (8-9:10AM UTC-4)

What can MIR learn from transfer learning in NLP?. Colin Raffel (UNC at Chapel Hill / Google Brain)

Oral Presentations 1A (9:10-9:30AM UTC-4)

  • Discovering Music Relations with Sequential Attention. Junyan Jiang, Gus Xia and Taylor Berg-Kirkpatrick

  • Lyrics Information Processing: Analysis, Generation, and Applications. Kento Watanabe and Masataka Goto

Posters Q&A 1A/1B (9:30-11AM UTC-4)

Video Playlists: Youtube | Bilibili

  • Discovering Music Relations with Sequential Attention. Junyan Jiang, Gus Xia and Taylor Berg-Kirkpatrick

  • Lyrics Information Processing: Analysis, Generation, and Applications. Kento Watanabe and Masataka Goto

  • Prediction of user listening contexts for music playlists. Jeong Choi, Anis Khlif and Elena Epure

  • Computational Linguistics Metrics for the Evaluation of Two-Part Counterpoint Generated with Neural Machine Translation. Stefano Kalonaris, Thomas McLachlan and Anna Aljanaki

  • BUTTER: A Representation Learning Framework for Bi-directional Music-Sentence Retrieval and Generation. Yixiao Zhang, Ziyu Wang, Dingsu Wang and Gus Xia

  • Unsupervised Melody Segmentation Based on a Nested Pitman-Yor Language Model. Shun Sawada, Kazuyoshi Yoshii and Keiji Hirata

  • Generation of lyrics lines conditioned on music audio clips. Olga Vechtomova, Gaurav Sahu and Dhruv Kumar.

  • Classification of Nostalgic Music Through LDA Topic Modeling and Sentiment Analysis of YouTube Comments in Japanese Songs. Kongmeng Liew, Yukiko Uchida, Nao Maeura and Eiji Aramaki.

  • Music autotagging as captioning. Tian Cai, Michael I Mandel and Di He.

Industry Session 1A (11AM-12PM UTC-4)

  • Music data processing for voice control. Rosa Stern & Alice Coucke (Sonos)

  • “Je ne parle pas anglais”, dealing with multilingualism in MIR. Elena Epure, Marion Baranes & Romain Henequin (Deezer)

  • Lean-back or lean-in? Fabien Gouyon (Pandora/SXM)

Keynote 2 (12:30-1:30PM UTC-4)

  • Universality and diversity in human song. Sam Mehr (Harvard Music Lab)

Oral Presentations 2A (1:30-2PM UTC-4)

  • Did You “Read” the Next Episode? Using Textual Cues for Predicting Podcast Popularity. Brihi Joshi, Shravika Mittal and Aditya Chetan

  • Symbolic Music Generation with Transformer-GANs. Aashiq Muhamed, Liang Li, Xingjian Shi, Rahul Suresh and Alexander Smola

  • An Information-based Model for Writing Style Analysis of Lyrics. Melesio Crespo-Sánchez, Edwin Aldana-Bobadilla, Iván López-Arévalo and Alejandro Molina-Villegas

Posters Q&A 2A/2B (2-3:30PM UTC-4)

Video Playlists: Youtube | Bilibili

  • Did You “Read” the Next Episode? Using Textual Cues for Predicting Podcast Popularity. Brihi Joshi, Shravika Mittal and Aditya Chetan

  • Using Latent Semantics of Playlist Titles and Descriptions to Enhance Music Recommendations. Yun Hao and J. Stephen Downie

  • Symbolic Music Generation with Transformer-GANs. Aashiq Muhamed, Liang Li, Xingjian Shi, Rahul Suresh and Alexander Smola

  • An Information-based Model for Writing Style Analysis of Lyrics. Melesio Crespo-Sánchez, Edwin Aldana-Bobadilla, Iván López-Arévalo and Alejandro Molina-Villegas

  • Hyperbolic Embeddings for Music Taxonomy. Maria Astefanoaei and Nicolas Collignon

  • Interacting with GPT-2 to Generate Controlled and Believable Musical Sequences in ABC Notation. Cariña Geerlings and Albert Meroño-Peñuela

  • Comparing Lyrics Features for Genre Recognition. Maximilian Mayerl, Michael Vötter, Manfred Moosleitner and Eva Zangerle.

  • MusicBERT - learning multi-modal representations for music and text. Federico Rossetto and Jeff Dalton.

Industry Session 2A (3:30-4:30PM UTC-4)

  • Inside a real world conversational music recommender. Tao Ye (Amazon)

  • Building a Personalized Voice Assistant for Music. Isaac Julien & Shuo Zhang (Bose)

  • The Spotify Podcasts Dataset. Sravana Reddy (Spotify)

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