Signal Processing, Uni Hamburg @sp_uhh
Research group of Prof. Timo Gerkmann with a focus on signal processing, speech and machine learning. inf.uni-hamburg.de/en/inst/ab/sp Hamburg, Germany Joined October 2020-
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🔍 Join Our Team! We have exciting open positions: 🎓 Postdoc: Data Science & AI for Speech & Audio 🎓 PhD/Postdoc: AI-based Speech & Audio 🎓 PhD: Diffusion Models for Speech Processing 🎓 3 PhD positions for Imaging & Speech 🔗 inf.uni-hamburg.de/en/inst/ab/sp/…
Our recent paper investigates SGMSE and Schrödinger bridge for speech enhancement. We achieve 3.70 in PESQ on Voicebank-Damand. 📰 arxiv.org/abs/2409.10753 🔊 sp-uhh.github.io/gen-se/
The Signal Processing group at the University of Hamburg is looking for PhD students and a postdoc in AI-based Speech and Audio Signal Processing. We have two openings available. Apply now and join our team. inf.uni-hamburg.de/en/inst/ab/sp/… #phdcandidate #postdocjobs
BUDDy: Single-Channel Blind Unsupervised Dereverberation with Diffusion Models We present a fully unsupervised method for blind speech dereverberation using a diffusion prior and a parametric subband filter Paper 📜 arxiv.org/abs/2405.04272 Audio/Code 🔊 uhh.de/sp-inf-buddy
This is what happens when you enhance an old WHAM! interview with SGMSE+ that has been trained on EARS-WHAM. 👉Further details about the new EARS dataset can be found here: sp-uhh.github.io/ears_dataset/ youtu.be/H5FiO0JxPK4?si…
𝗣𝗵𝗗 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 „𝗗𝗶𝗳𝗳𝘂𝘀𝗶𝗼𝗻-𝗕𝗮𝘀𝗲𝗱 𝗗𝗲𝗲𝗽 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 𝗳𝗼𝗿 𝗦𝗽𝗲𝗲𝗰𝗵 𝗦𝗶𝗴𝗻𝗮𝗹 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴“. Join us in pushing the state-of-the-art in this exciting field. Details and on how to apply: inf.uni-hamburg.de/en/inst/ab/sp/…
``Diffusion Models for Audio Restoration,'' Jean-Marie Lemercier, Julius Richter, Simon Welker, Eloi Moliner, Vesa V\"alim\"aki, Timo Gerkmann, ift.tt/hPW6pEG
Happy to announce five accepted papers at @ieeeICASSP #ICASSP2024. Hope to see you there! All papers and links to arxiv preprints can be found on our webpages inf.uni-hamburg.de/en/inst/ab/sp/…
We just opened a PhD or Postdoc position on AI-based speech and audio signal processing. Please see our webpage for details and on how to apply inf.uni-hamburg.de/en/inst/ab/sp/…
It had been a super nice ICASSP in Rhodes. We really enjoyed exchanging ideas with our peers. There are so many exciting things discussed in the community atm (diffusion, self-supervised, metrics, ...). Very much looking forward for the next events to come!
Happy to announce our two recently accepted IEEE/ACM TASL journals that show how score-based / diffusion models can be used for high quality signal improvement. Audio examples, paper and code are available here inf.uni-hamburg.de/en/inst/ab/sp/…
Happy to announce four papers at #INTERSPEECH2023 @ISCAInterspeech on diffusion models, SSL for emotion recognition, audio-visual speech enhancement, and dereverberation. See details on our webpages inf.uni-hamburg.de/en/inst/ab/sp/…
We offer an exciting #PhDposition on deep multi-microphone speech enhancement. Please find details on our webpages inf.uni-hamburg.de/en/inst/ab/sp/…
Our newly developed causal version of our recent work on diffusion-based generative models for speech enhancement arxiv.org/abs/2208.05830 has been ranked in the Top 5 of the #ICASSP2023 Speech Signal Improvement Challenge and will be presented @ieeeICASSP microsoft.com/en-us/research…
We will be presenting 7 papers @ieeeICASSP, on diffusion models, uncertainty estimation, and nonlinear joint spatial-spectral filtering, including our Top 5 contribution to the #ICASSP2023 Speech Signal Improvement Challenge inf.uni-hamburg.de/en/inst/ab/sp/…
Happy to announce 5 accepted papers for ICASSP 2023! They address in particular * Diffusion models * Nonlinear joint spatial-spectral filtering * Uncertainty Estimation in Speech Enhancement inf.uni-hamburg.de/en/inst/ab/sp/… #ICASSP2023
We are pleased to share our new work: „Speech Enhancement and Dereverberation with Diffusion-based Generative Models“ with exciting audio examples Pre-print: arxiv.org/abs/2208.05830 Audio examples: bit.ly/3Ai8pqT Code: github.com/sp-uhh/sgmse #diffusion
Great news: We receive the VDE ITG award 2022 for our contribution which motivates the use of DNNs for nonlinear joint spatial-spectral filtering to replace sequential linear spatial filtering + postfiltering in speech enhancement. Don't miss this paper uhh.de/inf-sp-nonline…
We are happy to announce 5 papers at Interspeech 2022 on speech enhancement and emotion recognition using e.g. Score Based Models, Bayesian DNNs, Transformers, End-to-End, and Deep Kalman See our webpages for details uhh.de/inf-sp #interspeech2022
Happy to announce 3 papers at #icassp2022 Customizable End-To-End Optimization Of Online Neural Network-Supported Dereverberation For Hearing Devices Integrating Statistical Uncertainty Into Neural Network-Based Speech Enhancement Deep Iterative Phase Retrieval For Ptychography
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