3 citations · 3 across the 5 of their papers we have counts for
5 papers
Ethics Statements in AI Music Papers: The Effective and the Ineffective
Julia Barnett, Patrick O'Reilly, Jason Brent Smith +2
While research in AI methods for music generation and analysis has grown in scope and impact, AI researchers' engagement with the ethical consequences of this work has not kept pac…
The Rhythm In Anything: Audio-Prompted Drums Generation with Masked Language Modeling
Patrick O'Reilly, Julia Barnett, Hugo Flores García +4
Musicians and nonmusicians alike use rhythmic sound gestures, such as tapping and beatboxing, to express drum patterns. While these gestures effectively communicate musical ideas,…
Sound Check: Auditing Audio Datasets
William Agnew, Julia Barnett, Annie Chu +6
Generative audio models are rapidly advancing in both capabilities and public utilization -- several powerful generative audio models have readily available open weights, and some…
Text2FX: Harnessing CLAP Embeddings for Text-Guided Audio Effects
Annie Chu, Patrick O'Reilly, Julia Barnett +1
This work introduces Text2FX, a method that leverages CLAP embeddings and differentiable digital signal processing to control audio effects, such as equalization and reverberation,…
Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model
Julia Barnett, Hugo Flores Garcia, Bryan Pardo
Every artist has a creative process that draws inspiration from previous artists and their works. Today, "inspiration" has been automated by generative music models. The black box…