activity
20242026
collaborators

6 papers

eess.AS2026

Room Impulse Response Completion Using Signal-Prediction Diffusion Models Conditioned on Simulated Early Reflections

Zeyu Xu, Andreas Brendel, Albert G. Prinn +1

Room impulse responses (RIRs) are fundamental to audio data augmentation, acoustic signal processing, and immersive audio rendering. While geometric simulators such as the image so…

eess.AS2026

Robust Online Overdetermined Independent Vector Analysis Based on Bilinear Decomposition

Kang Chen, Xianrui Wang, Yichen Yang +6

Online blind source separation is essential for both speech communication and human-machine interaction. Among existing approaches, overdetermined independent vector analysis (Over…

eess.AS2025

DeePAQ: A Perceptual Audio Quality Metric Based On Foundational Models and Weakly Supervised Learning

Guanxin Jiang, Andreas Brendel, Pablo M. Delgado +1

This paper presents the Deep learning-based Perceptual Audio Quality metric (DeePAQ) for evaluating general audio quality. Our approach leverages metric learning together with the…

eess.AS2025

GAN-Based Multi-Microphone Spatial Target Speaker Extraction

Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel

Spatial target speaker extraction isolates a desired speaker's voice in multi-speaker environments using spatial information, such as the direction of arrival (DoA). Although recen…

eess.AS2025

Leveraging Discriminative Latent Representations for Conditioning GAN-Based Speech Enhancement

Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel

Generative speech enhancement methods based on generative adversarial networks (GANs) and diffusion models have shown promising results in various speech enhancement tasks. However…

eess.AS2024

GAN-Based Speech Enhancement for Low SNR Using Latent Feature Conditioning

Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel

Enhancing speech quality under adverse SNR conditions remains a significant challenge for discriminative deep neural network (DNN)-based approaches. In this work, we propose DisCoG…