A Demand-Driven Perspective on Generative Audio AI

no code implementations • 10 Jul 2023 • Sangshin Oh, Minsung Kang, Hyeongi Moon, Keunwoo Choi, Ben Sangbae Chon

To achieve successful deployment of AI research, it is crucial to understand the demands of the industry.

Audio Generation

FALL-E: A Foley Sound Synthesis Model and Strategies

1 code implementation • 16 Jun 2023 • Minsung Kang, Sangshin Oh, Hyeongi Moon, Kyungyun Lee, Ben Sangbae Chon

This paper introduces FALL-E, a foley synthesis system and its training/inference strategies.

Language Modelling Prompt Engineering +1

A Proposal for Foley Sound Synthesis Challenge

no code implementations • 21 Jul 2022 • Keunwoo Choi, Sangshin Oh, Minsung Kang, Brian McFee

"Foley" refers to sound effects that are added to multimedia during post-production to enhance its perceived acoustic properties, e. g., by simulating the sounds of footsteps, ambient environmental sounds, or visible objects on the screen.

ReCAB-VAE: Gumbel-Softmax Variational Inference Based on Analytic Divergence

no code implementations • 9 May 2022 • Sangshin Oh, Seyun Um, Hong-Goo Kang

In this work, we present a relaxed categorical analytic bound (ReCAB), a novel divergence-like metric which corresponds to the upper bound of the Kullback-Leibler divergence (KLD) of a relaxed categorical distribution.

Speech Synthesis Text-To-Speech Synthesis +1