1 citations · 2 across the 5 of their papers we have counts for
5 papers
Velocity Prediction in Automatic Guitar Transcription
Jackson Loth, Xavier Riley, Simon Dixon +1
Automatic Music Transcription (AMT) models have achieved a high level of success in polyphonic transcription of various instruments. Velocity, typically a measure of note intensity…
GuitarFlow: Realistic Electric Guitar Synthesis From Tablatures via Flow Matching and Style Transfer
Jackson Loth, Pedro Sarmento, Mark Sandler +1
Music generation in the audio domain using artificial intelligence (AI) has witnessed steady progress in recent years. However for some instruments, particularly the guitar, contro…
GOAT: A Large Dataset of Paired Guitar Audio Recordings and Tablatures
Jackson Loth, Pedro Sarmento, Saurjya Sarkar +3
In recent years, the guitar has received increased attention from the music information retrieval (MIR) community driven by the challenges posed by its diverse playing techniques a…
Between the AI and Me: Analysing Listeners' Perspectives on AI- and Human-Composed Progressive Metal Music
Pedro Sarmento, Jackson Loth, Mathieu Barthet
Generative AI models have recently blossomed, significantly impacting artistic and musical traditions. Research investigating how humans interact with and deem these models is ther…
ProgGP: From GuitarPro Tablature Neural Generation To Progressive Metal Production
Jackson Loth, Pedro Sarmento, CJ Carr +2
Recent work in the field of symbolic music generation has shown value in using a tokenization based on the GuitarPro format, a symbolic representation supporting guitar expressive…