Authors
- Shoko Araki
- Nobutaka Ito
- Reinhold Haeb-Umbach
- Gordon Wichern
- Zhong-Qiu Wang
- Yuki Mitsufuji
Venue
- ICASSP-25
Date
- 2025
30+ Years of Source Separation Research: Achievements and Future Challenges
Shoko Araki
Nobutaka Ito
Reinhold Haeb-Umbach
Gordon Wichern
Zhong-Qiu Wang
ICASSP-25
2025
Abstract
Source separation (SS) of acoustic signals is a research field that emerged in the mid-1990s and has flourished ever since. On the occasion of ICASSP's 50th anniversary, we review the major contributions and advancements in the past three decades in the speech, audio, and music SS research field. We will cover both single- and multi-channel SS approaches. We will also look back on key efforts to foster a culture of scientific evaluation in the research field, including challenges, performance metrics, and datasets. We will conclude by discussing current trends and future research directions.
Related Publications
Although recent speech processing technologies have achieved significant improvements in objective metrics, there still remains a gap in human perceptual quality. This paper proposes Diffiner, a novel solution that utilizes the powerful generative capability of diffusion mod…
Recent advances in Video-to-Audio (V2A) generation have achieved impressive perceptual quality and temporal synchronization, yet most models remain appearance-driven, capturing visual-acoustic correlations without considering the physical factors that shape real-world sounds…
MeanFlow (MF) is a diffusion-motivated generative model that enables efficient few-step generation by learning long jumps directly from noise to data. In practice, it is often used as a latent MF by leveraging the pre-trained Stable Diffusion variational autoencoder (SD-VAE)…
JOIN US
Shape the Future of AI with Sony AI
We want to hear from those of you who have a strong desire
to shape the future of AI.



