Darius Petermann
Computer Science · Indiana University
Publications
26
Citations
110
Est. group size
—
Recurring co-author estimate
Active years
6
Publishing since 2020
Darius Petermann works on machine learning methods for processing sound, with a particular focus on audio source separation\u2014the task of isolating individual sounds (such as speech, music, and sound effects) from mixed recordings. Recent work also covers neural audio coding (compressing audio efficiently), tools for evaluating speech and music systems, and generating images from sounds.
Publication activity began around 2020 and was steady at about six papers per year through 2021-2023, with a somewhat lower rate in 2024-2025.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music
2025
- Seeing Sound: Assembling Sounds from Visuals for Audio-to-Image Generation
arXiv (Cornell University) · 2025
- VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music
arXiv (Cornell University) · 2024
- Hyperbolic Distance-Based Speech Separation
2024
- Hyperbolic Distance-Based Speech Separation
arXiv (Cornell University) · 2024
- Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks
IEEE/ACM Transactions on Audio Speech and Language Processing · 2023
- Hyperbolic Audio Source Separation
2023
- Librispeech Slakh Unmix (LSX)
Zenodo (CERN European Organization for Nuclear Research) · 2023
- Librispeech Slakh Unmix (LSX)
Zenodo (CERN European Organization for Nuclear Research) · 2023
- Native Multi-Band Audio Coding Within Hyper-Autoencoded Reconstruction Propagation Networks
2023
- Native Multi-Band Audio Coding within Hyper-Autoencoded Reconstruction Propagation Networks
arXiv (Cornell University) · 2023
- The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · 2022
- A Deep-Learning Based Framework for Source Separation, Analysis, and Synthesis of Choral Ensembles
Frontiers in Signal Processing · 2022
- Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks
arXiv (Cornell University) · 2022
- Hyperbolic Audio Source Separation
arXiv (Cornell University) · 2022
- arXiv (Cornell University)×11
- Zenodo (CERN European Organization for Nuclear Research)×6
- ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)×2
- IEEE/ACM Transactions on Audio Speech and Language Processing×1
- Frontiers in Signal Processing×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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