4 papers
MGE-LDM: Joint Latent Diffusion for Simultaneous Music Generation and Source Extraction
Yunkee Chae, Kyogu Lee
We present MGE-LDM, a unified latent diffusion framework for simultaneous music generation, source imputation, and query-driven source separation. Unlike prior approaches constrain…
Song Form-aware Full-Song Text-to-Lyrics Generation with Multi-Level Granularity Syllable Count Control
Yunkee Chae, Eunsik Shin, Suntae Hwang +2
Lyrics generation presents unique challenges, particularly in achieving precise syllable control while adhering to song form structures such as verses and choruses. Conventional li…
Towards Bitrate-Efficient and Noise-Robust Speech Coding with Variable Bitrate RVQ
Yunkee Chae, Kyogu Lee
Residual Vector Quantization (RVQ) has become a dominant approach in neural speech and audio coding, providing high-fidelity compression. However, speech coding presents additional…
Variable Bitrate Residual Vector Quantization for Audio Coding
Yunkee Chae, Woosung Choi, Yuhta Takida +8
Recent state-of-the-art neural audio compression models have progressively adopted residual vector quantization (RVQ). Despite this success, these models employ a fixed number of c…