Cosy Companies
Data viz for company addresses
Posts by Collection
portfolio
Overtone Documentation
Early example of a Clojure project
PFI Explorer
PFI explorer for hack day
Sonic Pi core team
Sonic Pi core team
Wikidata Family Tree Explorer
UI for wikidata
publications
Evaluating distributed time synchronization for musical applications using Ableton Link
Published in None, 2018
My MSc thesis. I used the Jepsen framework to look at various aspects of the Ableton Link system for synchronizing musical timing.
Recommended citation: https://github.com/xavriley/msc/blob/master/template.pdf
FiloBass: A Dataset and Corpus Based Study of Jazz Basslines
Published in ISMIR, 2023
We present FiloBass: a novel corpus of music scores and annotations which focuses on the important but often overlooked role of the double bass in jazz accompaniment
Recommended citation: https://arxiv.org/pdf/2311.02023
CREPE Notes: A new method for segmenting pitch contours into discrete notes
Published in SMC, 2023
Building on CREPE, a state-of-the-art monophonic pitch tracking solution based on a simple neural network, we propose a simple and effective method for post-processing CREPE’s output to achieve monophonic note segmentation.
Recommended citation: Riley, Xavier and Simon Dixon (2023). "CREPE Notes: A new method for segmenting pitch contours into discrete notes" Proceedings of the 20th Sound and Music Computing Conference. Stockholm, Sweden pp. 1–5. https://arxiv.org/pdf/2311.08884
High Resolution Guitar Transcription via Domain Adaptation
Published in ICASSP, 2024
We propose the use of a high-resolution piano transcription model to train a new guitar transcription model. The resulting model obtains state-of-the-art transcription results on GuitarSet in a zero-shot context, improving on previously published methods.
Recommended citation: https://arxiv.org/pdf/2402.15258
Reconstructing the Charlie Parker Omnibook using an audio-to-score automatic transcription pipeline
Published in Sound and Music Computing Conference 2024, 2024
We propose a new transcription pipeline to reconstruct the Charlie Parker Omnibook directly from audio, including a source separation model for saxophone, a MIDI transcription model for solo saxophone, and an adaptation of an existing MIDI-to-score method. We also provide an enhanced dataset of Charlie Parker transcriptions as score-audio pairs with accurate MIDI alignments and downbeat annotations.
Recommended citation: Riley, Xavier, and Simon Dixon (2024). "Reconstructing the Charlie Parker Omnibook using an audio-to-score automatic transcription pipeline" Proceedings of the Sound and Music Computing Conference 2024 https://arxiv.org/abs/2405.16687
MIDI-to-Tab: Guitar Tablature Inference via Masked Language Modeling
Published in ISMIR, 2024
We introduce a novel deep learning solution to symbolic guitar tablature estimation using an encoder-decoder Transformer model trained in a masked language modeling paradigm. Our model, pre-trained on DadaGP and fine-tuned on professionally transcribed performances, significantly outperforms competing algorithms in a user study assessing tablature playability.
Recommended citation: Edwards, Drew, Xavier Riley, Pedro Sarmento, and Simon Dixon (2024). "MIDI-to-Tab: Guitar Tablature Inference via Masked Language Modeling" Proceedings of the 25th International Society for Music Information Retrieval Conference https://arxiv.org/abs/2408.05024
GAPS: A Large and Diverse Classical Guitar Dataset and Benchmark Transcription Model
Published in ISMIR, 2024
We introduce GAPS (Guitar-Aligned Performance Scores), a new dataset of classical guitar performances, and a benchmark guitar transcription model that achieves state-of-the-art performance on GuitarSet in both supervised and zero-shot settings. GAPS is the largest dataset of real guitar audio, containing 14 hours of freely available audio-score aligned pairs, recorded in diverse conditions by over 200 performers, together with high-resolution note-level MIDI alignments and performance videos.These enable us to train a state-of-the-art model for automatic transcription of solo guitar recordings which can generalise well to real world audio that is unseen during training.
Recommended citation: Riley, Xavier, Zixun Guo, Drew Edwards, and Simon Dixon (2024). "GAPS: A Large and Diverse Classical Guitar Dataset and Bench- mark Transcription Model" Proceedings of the 25th International Society for Music Information Retrieval Conference https://www.eecs.qmul.ac.uk/~simond/pub/2024/RileyEtAl-ISMIR-2024.pdf
talks
Coding Music: As easy as Pi
Published:
Had a speaker slot at the WXG web conference in Guildford. Presented an introduction to programming music with Sonic Pi in which I demo a few of my experiments. The video/audio didn’t come out too well but the talk was well received I think.
Live Coding in the Classroom
Published:
Co-presented talk on Sonic Pi with the lead developer Sam Aaron. I think the original video has been taken down now but my bit is here:
Bath Ruby 2015: Lightning Talk
Published:
Lightning “talk” in which I managed to do no talking! A 5 minute live coded piece starting from scratch, with sampled voices from the other Bath Ruby presenters.
Bath Ruby 2016: Rocking Out in Ruby
Published:
My keynote presentation at Bath Ruby 2016