1 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
A Demand-Driven Perspective on Generative Audio AI
Sangshin Oh, Minsung Kang, Hyeongi Moon +2
To achieve successful deployment of AI research, it is crucial to understand the demands of the industry. In this paper, we present the results of a survey conducted with professio…
FALL-E: A Foley Sound Synthesis Model and Strategies
Minsung Kang, Sangshin Oh, Hyeongi Moon +2
This paper introduces FALL-E, a foley synthesis system and its training/inference strategies. The FALL-E model employs a cascaded approach comprising low-resolution spectrogram gen…
ReCAB-VAE: Gumbel-Softmax Variational Inference Based on Analytic Divergence
Sangshin Oh, Seyun Um, Hong-Goo Kang
The Gumbel-softmax distribution, or Concrete distribution, is often used to relax the discrete characteristics of a categorical distribution and enable back-propagation through dif…
Emotional speech synthesis with rich and granularized control
Se-Yun Um, Sangshin Oh, Kyungguen Byun +3
This paper proposes an effective emotion control method for an end-to-end text-to-speech (TTS) system. To flexibly control the distinct characteristic of a target emotion category,…