This episode brings recommendations from the 2019 ISMIR conference at TUDelft in the Netherlands. A number of contributors, old and new, highlighted papers that had caught their attention. 

Note: At ISMIR, all accepted papers were presented via a short 4 minute talk and a poster. This arrangement made it possible to keep all presentations in a single track. All papers and permited talks are posted on the ISMIR site.

Time Stamps

* [0:01:51] Matan’s rec* [0:07:27] Rachel’s rec* [0:10:51] Andrew’s rec* [0:15:20] Ashley and Felicia’s rec* [0:19:59] Néstor’s rec* [0:26:55] Tejaswinee’s rec* [0:31:13] Brian’s rec* [0:36:06] Finn’s recs

Show notes

* Matan Gover recommends [A13] Conditioned-U-Net: Introducing a Control Mechanism in the U-Net for Multiple Source Separations by Gabriel Meseguer Brocal and Geoffroy Peeters (paper, presentation)* Andrew Demetriou recommends [F10] Tunes Together: Perception and Experience of Collaborative Playlists by So Yeon Park; Audrey Laplante; Jin Ha Lee; Blair Kaneshiro (paper, presentation)* Tejaswinee Kelkar recommends [B03] Estimating Unobserved Audio Features for Target-Based Orchestration by Jon Gillick; Carmine-Emanuele Cella; David Bamman (paper, presentation)* Ashley Burgoyne and Felicia Villalobos recommend [E13] SAMBASET: A Dataset of Historical Samba de Enredo Recordings for Computational Music Analysis by Lucas Maia; Magdalena Fuentes; Luiz Biscainho; Martín Rocamora; Slim Essid (paper, presentation)* Néstor Nápoles López recommends the anniversary paper [E-00] 20 Years of Automatic Chord Recognition from Audio by Johan Pauwels; Ken O'Hanlon; Emilia Gomez; Mark B. Sandler (paper, presentation)* Rachel Bittner recommends [A06] Cover Detection with Dominant Melody Embeddings by Guillaume Doras; Geoffroy Peeters (paper, presentation)* Brian McFee recommends [E-06] FMP Notebooks: Educational Material for Teaching and Learning Fundamentals of Music Processing by Meinard Müller; Frank Zalkow (paper, presentation, webpage)* And Finn’s rec:* [D-12] AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing  By Shuhei Tsuchida; Satoru Fukayama; Masahiro Hamasaki; Masata...