At the awards ceremony for the AES 53rd Conference on Semantic Audio, the paper by Son Tran, Daniel Wolff, Tillman Weyde, and Artur Garcez entitled “Feature preprocessing using RBMs for music similarity learning” won the prize for Fully-Reproducible Work, as part of the Prizes for Reproducibility in Semantic Audio Research, sponsored by the EPSRC-funded SoundSoftware Project. Congratulations to all involved!