Authors

Venue

Date

Share

30+ Years of Source Separation Research: Achievements and Future Challenges

Shoko Araki

Nobutaka Ito

Reinhold Haeb-Umbach

Gordon Wichern

Zhong-Qiu Wang

Yuki Mitsufuji

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

Can Large Language Models Predict Audio Effects Parameters from Natural Language?

WASPAA, 2025
Seungheon Doh, Junghyun Koo*, Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Juhan Nam, Yuki Mitsufuji

In music production, manipulating audio effects (Fx) parameters through natural language has the potential to reduce technical barriers for non-experts. We present LLM2Fx, a framework leveraging Large Language Models (LLMs) to predict Fx parameters directly from textual desc…

Large-Scale Training Data Attribution for Music Generative Models via Unlearning

ICML, 2025
Woosung Choi, Junghyun Koo*, Kin Wai Cheuk, Joan Serrà, Marco A. Martínez-Ramírez, Yukara Ikemiya, Naoki Murata, Yuhta Takida, Wei-Hsiang Liao, Yuki Mitsufuji

This paper explores the use of unlearning methods for training data attribution (TDA) in music generative models trained on large-scale datasets. TDA aims to identify which specific training data points contributed to the generation of a particular output from a specific mod…

Fx-Encoder++: Extracting Instrument-Wise Audio Effects Representations from Mixtures

ISMIR, 2025
Yen-Tung Yeh, Junghyun Koo*, Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Yi-Hsuan Yang, Yuki Mitsufuji

General-purpose audio representations have proven effective across diverse music information retrieval applications, yet their utility in intelligent music production remains limited by insufficient understanding of audio effects (Fx). Although previous approaches have empha…

  • HOME
  • Publications
  • 30+ Years of Source Separation Research: Achievements and Future Challenges

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.