1 citations · 1 across the 9 of their papers we have counts for
10 papers
Accurate Plate Reverb Parameter Estimation Using Two-Stage Evolutionary Search
Byunghoo Park, Jayeon Yi, Takyoung Kim +1
We describe our submission to Task A of the 1st DAFx parameter estimation challenge. The task is to recover the six physical parameters of a simulated metal-plate reverberator -- i…
Singer-Informed Vocal Source Separation for Multi-Singer Music Mixtures
Jocelyn Xu, Minje Kim
Music source separation systems typically extract a single vocal track and do not distinguish between multiple singers. We study singer-informed vocal source separation for multi-s…
Gencho: Room Impulse Response Generation from Reverberant Speech and Text via Diffusion Transformers
Jackie Lin, Jiaqi Su, Nishit Anand +3
Blind room impulse response (RIR) estimation is a core task for capturing and transferring acoustic properties; yet existing methods often suffer from limited modeling capability a…
From Hallucination to Articulation: Language Model-Driven Losses for Ultra Low-Bitrate Neural Speech Coding
Jayeon Yi, Minje Kim
``Phoneme Hallucinations (PH)'' commonly occur in low-bitrate DNN-based codecs. It is the generative decoder's attempt to synthesize plausible outputs from excessively compressed t…
Uncovering EEG Patterns Consistently Associated with Cybersickness Discomfort Using Deep Learning Interpretability Maps
Jacqueline Yau, Katherine J. Mimnaugh, Pawel Augustynowicz +9
Uncomfortable sensations similar to motion sickness, called cybersickness, can develop when using Virtual Reality (VR) head-mounted displays. Cybersickness poses a hindrance to gre…
PromptSep: Generative Audio Separation via Multimodal Prompting
Yutong Wen, Ke Chen, Prem Seetharaman +7
Recent breakthroughs in language-queried audio source separation (LASS) have shown that generative models can achieve higher separation audio quality than traditional masking-based…
Low-Resource Audio Codec (LRAC): 2025 Challenge Description
Kamil Wojcicki, Yusuf Ziya Isik, Laura Lechler +8
While recent neural audio codecs deliver superior speech quality at ultralow bitrates over traditional methods, their practical adoption is hindered by obstacles related to low-res…
Combolutional Neural Networks
Cameron Churchwell, Minje Kim, Paris Smaragdis
Selecting appropriate inductive biases is an essential step in the design of machine learning models, especially when working with audio, where even short clips may contain million…
Adaptive Slimming for Scalable and Efficient Speech Enhancement
Riccardo Miccini, Minje Kim, Clément Laroche +2
Speech enhancement (SE) enables robust speech recognition, real-time communication, hearing aids, and other applications where speech quality is crucial. However, deploying such sy…
User-guided Generative Source Separation
Yutong Wen, Minje Kim, Paris Smaragdis
Music source separation (MSS) aims to extract individual instrument sources from their mixture. While most existing methods focus on the widely adopted four-stem separation setup (…