5 papers · 1 filter
Reconstruct! Don't Encode: Self-Supervised Representation Reconstruction Loss for High-Intelligibility and Low-Latency Streaming Neural Audio Codec
Junhyeok Lee, Xiluo He, Jihwan Lee +6
Neural audio codecs optimized for mel-spectrogram reconstruction often fail to preserve intelligibility. While semantic encoder distillation improves encoded representations, it do…
Super Monotonic Alignment Search
Junhyeok Lee, Hyeongju Kim
Monotonic alignment search (MAS), introduced by Glow-TTS, is one of the most popular algorithm in text-to-speech to estimate unknown alignments between text and speech. Since this…
DualSpeech: Enhancing Speaker-Fidelity and Text-Intelligibility Through Dual Classifier-Free Guidance
Jinhyeok Yang, Junhyeok Lee, Hyeong-Seok Choi +3
Text-to-Speech (TTS) models have advanced significantly, aiming to accurately replicate human speech's diversity, including unique speaker identities and linguistic nuances. Despit…
JenGAN: Stacked Shifted Filters in GAN-Based Speech Synthesis
Hyunjae Cho, Junhyeok Lee, Wonbin Jung
Non-autoregressive GAN-based neural vocoders are widely used due to their fast inference speed and high perceptual quality. However, they often suffer from audible artifacts such a…
Diversifying and Expanding Frequency-Adaptive Convolution Kernels for Sound Event Detection
Hyeonuk Nam, Seong-Hu Kim, Deokki Min +2
Frequency dynamic convolution (FDY conv) has shown the state-of-the-art performance in sound event detection (SED) using frequency-adaptive kernels obtained by frequency-varying co…