1 citations · 3 across the 5 of their papers we have counts for
6 papers
Don't CLAP: Are Music-Text Models Bag-of-Words?
Yuan-Chiao Cheng, Alexander Lerch
Text-to-music systems are assessed on audio quality and on how faithfully the music follows its prompt, and the CLAP score, the cosine similarity between a music-text model's audio…
H2H Music Improv: A Communication Model and Audio-Visual Dataset for Music Improvisation
Aleksandra Teng Ma, Anthony Cammarota, Jiayi Wang +4
Current real-time AI improvisation systems lack the communication awareness human musicians rely on: rather than treating communication as a foundational algorithm design concern,…
FoleySet: A Multi-Level Human-Annotated Foley Sound Dataset
Sunshiyu Wang, Alexander Lerch
In audiovisual post-production, Foley refers to synchronous sound effects associated with human actions, such as footsteps, cloth rustle, and prop handling, that are recreated to m…
Survey on the Evaluation of Generative Models in Music
Alexander Lerch, Claire Arthur, Nick Bryan-Kinns +3
Research on generative systems in music has seen considerable attention and growth in recent years. A variety of attempts have been made to systematically evaluate such systems. We…
Enhancing Video Music Recommendation with Transformer-Driven Audio-Visual Embeddings
Shimiao Liu, Alexander Lerch
A fitting soundtrack can help a video better convey its content and provide a better immersive experience. This paper introduces a novel approach utilizing self-supervised learning…
AQUATK: An Audio Quality Assessment Toolkit
Ashvala Vinay, Alexander Lerch
Recent advancements in Neural Audio Synthesis (NAS) have outpaced the development of standardized evaluation methodologies and tools. To bridge this gap, we introduce AquaTk, an op…