3 papers
cs.LG2020
NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity
Sang-gil Lee, Sungwon Kim, Sungroh Yoon
Normalizing flows (NFs) have become a prominent method for deep generative models that allow for an analytic probability density estimation and efficient synthesis. However, a flow…
eess.AS2020
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
Jaehyeon Kim, Sungwon Kim, Jungil Kong +1
Recently, text-to-speech (TTS) models such as FastSpeech and ParaNet have been proposed to generate mel-spectrograms from text in parallel. Despite the advantage, the parallel TTS…
cs.SD2018
FloWaveNet : A Generative Flow for Raw Audio
Sungwon Kim, Sang-gil Lee, Jongyoon Song +2
Most modern text-to-speech architectures use a WaveNet vocoder for synthesizing high-fidelity waveform audio, but there have been limitations, such as high inference time, in its p…