Julius Richter
@JuliusRichter13
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RT @ArxivSound: ``Normalize Everything: A Preconditioned Magnitude-Preserving Architecture for Diffusion-Based Speech Enhancement,'' Julius….
arxiv.org
This paper presents a new framework for diffusion-based speech enhancement. Our method employs a Schroedinger bridge to transform the noisy speech distribution into the clean speech distribution....
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Check out the slides here: Please note that the PDF is 36 MB in size due to its audio and video content, and it is best viewed using Acrobat Reader.
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Join me tomorrow for a webinar on "Generative Audio Restoration in Multimodal Applications"! .I'll introduce the tractable Schrödinger bridge and discuss the differences between flow matching and score-based methods.
signalprocessingsociety.org
Date: 22 April 2025 Time: 11:00 AM ET (New York Time) Presenter(s): Mr. Julius Richter
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Will present our paper, "Investigating Training Objectives for Generative Speech Enhancement" at #ICASSP2025!.🗓 Wed, 5:00-6:30 PM (AASP-P12).🔊 Discussing diffusion bridges (Schrödinger bridge) & connections to score-based models—let’s chat!
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🎉 Excited to announce that our paper got accepted at #ICASSP2025! We achieved state-of-the-art performance in PESQ on VB-DMD (yes, we're still using this benchmark 😂). Plus, our method shines on EARS-WHAM at 48 kHz! Check it out: 🚀📈 #GenertiveAI.
github.com
Score-based Generative Models (Diffusion Models) for Speech Enhancement and Dereverberation - sp-uhh/sgmse
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Presentation day!. I am going to present our contribution of Team Hamburgers 🍔 to the URGENT Challenge. NeurIPS, Saturday Dec 14, 3:45 pm, West Meeting Room 215, 216. @NeurIPSConf
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🗣️ Tomorrow I will be presenting a 𝗗𝗲𝗺𝗼 𝗼𝗻 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗦𝗽𝗲𝗲𝗰𝗵 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗺𝗲𝗻𝘁. NeurIPS: Saturday, Dec 14, 4:15 pm at West Meeting Room 114, 115. Hope to see you there! . Also feel free to try the Demo for yourself: .🔗
github.com
Diffusion-based Speech Enhancement: Demonstration of Performance and Generalization - sp-uhh/gen-se-demo
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RT @shinjiw_at_cmu: We are thrilled to announce the Interspeech 2025 URGENT Challenge, starting on 11/15! .Join us in building universal sp….
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RT @ArxivSound: ``Non-intrusive Speech Quality Assessment with Diffusion Models Trained on Clean Speech,'' Danilo de Oliveira, Julius Richt….
arxiv.org
Diffusion models have found great success in generating high quality, natural samples of speech, but their potential for density estimation for speech has so far remained largely unexplored. In...
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RT @sp_uhh: 🔍 Join Our Team! We have exciting open positions: . 🎓 Postdoc: Data Science & AI for Speech & Audio .🎓 PhD/Postdoc: AI-based….
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I will be presenting a demo on generative speech enhancement at the Audio Imagination @NeurIPSConf 2024 workshop. Just in time for the acceptance notification, we have released the code for our recent submission including the Schrödinger bridge approach:
github.com
Score-based Generative Models (Diffusion Models) for Speech Enhancement and Dereverberation - sp-uhh/sgmse
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Our recent paper investigates SGMSE and Schrödinger bridge for speech enhancement. We achieve 3.70 in PESQ on Voicebank-Damand. 📰 🔊
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Thank you @ISCAInterspeech for a great time in Kos! It was my pleasure to present the EARS dataset. Go and check it out: .🔗
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RT @AlexRichardCS: Working on your next big speech paper but still looking for a suitable dataset?.Check out EARS: 100h of full-band expres….
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RT @sp_uhh: This is what happens when you enhance an old WHAM! interview with SGMSE+ that has been trained on EARS-WHAM. 👉Further details….
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Our research group is offering a PhD position on "Diffusion-Based Deep Generative Models for Speech Signal Processing" .🔗
uni-hamburg.de
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RT @ArxivSound: ``Diffusion Models for Audio Restoration,'' Jean-Marie Lemercier, Julius Richter, Simon Welker, Eloi Moliner, Vesa V\"alim\….
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RT @sp_uhh: We offer an exciting #PhDposition on deep multi-microphone speech enhancement. Please find details on our webpages. https://t.co….
inf.uni-hamburg.de
Research Associate / wissenschaftlicher Mitarbeiter
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RT @ArxivSound: ``StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberation. (arXiv:2212.11851v1 [h….
arxiv.org
Diffusion models have shown a great ability at bridging the performance gap between predictive and generative approaches for speech enhancement. We have shown that they may even outperform their...
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