4 papers
EmoSphere-TTS: Emotional Style and Intensity Modeling via Spherical Emotion Vector for Controllable Emotional Text-to-Speech
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +2
Despite rapid advances in the field of emotional text-to-speech (TTS), recent studies primarily focus on mimicking the average style of a particular emotion. As a result, the abili…
Illuminating Salient Contributions in Neuron Activation with Attribution Equilibrium
Woo-Jeoung Nam, Seong-Whan Lee
With the remarkable success of deep neural networks, there is a growing interest in research aimed at providing clear interpretations of their decision-making processes. In this pa…
Accelerating High-Fidelity Waveform Generation via Adversarial Flow Matching Optimization
Sang-Hoon Lee, Ha-Yeong Choi, Seong-Whan Lee
This paper introduces PeriodWave-Turbo, a high-fidelity and high-efficient waveform generation model via adversarial flow matching optimization. Recently, conditional flow matching…
PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation
Sang-Hoon Lee, Ha-Yeong Choi, Seong-Whan Lee
Recently, universal waveform generation tasks have been investigated conditioned on various out-of-distribution scenarios. Although GAN-based methods have shown their strength in f…