8 papers
Uncovering Patterns of Brain Activity from EEG Data Consistently Associated with Cybersickness Using Neural Network Interpretability Maps
Jacqueline Yau, Katherine J. Mimnaugh, Evan G. Center +6
Cybersickness poses a serious challenge for users of virtual reality (VR) technology. Consequently, there has been significant effort to track its occurrence during VR use with pas…
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…
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…