35 citations · 60 across the 10 of their papers we have counts for
10 papers
PAS-SE: Personalized Auxiliary-Sensor Speech Enhancement for Voice Pickup in Hearables
Mattes Ohlenbusch, Mikolaj Kegler, Marko Stamenovic
Speech enhancement for voice pickup in hearables aims to improve the user's voice by suppressing noise and interfering talkers, while maintaining own-voice quality. For single-chan…
CATSE: A Context-Aware Framework for Causal Target Sound Extraction
Shrishail Baligar, Mikolaj Kegler, Bryce Irvin +2
Target Sound Extraction (TSE) focuses on the problem of separating sources of interest, indicated by a user's cue, from the input mixture. Most existing solutions operate in an off…
Latent CLAP Loss for Better Foley Sound Synthesis
Tornike Karchkhadze, Hassan Salami Kavaki, Mohammad Rasool Izadi +5
Foley sound generation, the art of creating audio for multimedia, has recently seen notable advancements through text-conditioned latent diffusion models. These systems use multimo…
Two-Step Knowledge Distillation for Tiny Speech Enhancement
Rayan Daod Nathoo, Mikolaj Kegler, Marko Stamenovic
Tiny, causal models are crucial for embedded audio machine learning applications. Model compression can be achieved via distilling knowledge from a large teacher into a smaller stu…
Self-Supervised Learning for Speech Enhancement through Synthesis
Bryce Irvin, Marko Stamenovic, Mikolaj Kegler +1
Modern speech enhancement (SE) networks typically implement noise suppression through time-frequency masking, latent representation masking, or discriminative signal prediction. In…
BYOL-S: Learning Self-supervised Speech Representations by Bootstrapping
Gasser Elbanna, Neil Scheidwasser-Clow, Mikolaj Kegler +3
Methods for extracting audio and speech features have been studied since pioneering work on spectrum analysis decades ago. Recent efforts are guided by the ambition to develop gene…
Hybrid Handcrafted and Learnable Audio Representation for Analysis of Speech Under Cognitive and Physical Load
Gasser Elbanna, Alice Biryukov, Neil Scheidwasser-Clow +5
As a neurophysiological response to threat or adverse conditions, stress can affect cognition, emotion and behaviour with potentially detrimental effects on health in the case of s…
SERAB: A multi-lingual benchmark for speech emotion recognition
Neil Scheidwasser-Clow, Mikolaj Kegler, Pierre Beckmann +1
Recent developments in speech emotion recognition (SER) often leverage deep neural networks (DNNs). Comparing and benchmarking different DNN models can often be tedious due to the…
Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing
Pierre Beckmann, Mikolaj Kegler, Milos Cernak
Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech…
Deep speech inpainting of time-frequency masks
Mikolaj Kegler, Pierre Beckmann, Milos Cernak
Transient loud intrusions, often occurring in noisy environments, can completely overpower speech signal and lead to an inevitable loss of information. While existing algorithms fo…