EURASIP Journal on Audio, Speech, and Music Processing

EURASIP Journal on Audio, Speech, and Music Processing
Title	EURASIP Journal on Audio, Speech, and Music Processing
Discipline	Audio engineering; Speech processing; Music information retrieval
Abbreviation	EURASIP J. Audio Speech Music Process.
History	2001–present
Frequency	Continuous

EURASIP Journal on Audio, Speech, and Music Processing is an open-access, peer-reviewed scholarly journal that publishes research on signal processing as applied to audio, speech, and music. The journal serves an international audience of researchers and practitioners connected to organizations such as European Association for Signal Processing, IEEE, International Speech Communication Association, Audio Engineering Society, and International Society for Music Information Retrieval. It sits within the broader ecosystem that includes publications like IEEE Transactions on Audio, Speech, and Language Processing, Journal of the Acoustical Society of America, Computer Music Journal, Signal Processing, and Pattern Recognition Letters.

History

The journal was launched in the early 21st century under the auspices of EURASIP to provide a dedicated venue comparable to IEEE Signal Processing Magazine and ACM Transactions on Multimedia Computing, Communications, and Applications. Its foundation drew on longstanding communities exemplified by conferences such as ICASSP, INTERSPEECH, MIR: Music Information Retrieval Evaluation eXchange, and institutions including École Polytechnique Fédérale de Lausanne, Massachusetts Institute of Technology, University of Cambridge, University of Oxford, and Technische Universität München. Over time it aligned with editorial practices similar to Elsevier-hosted journals and open-access publishers like SpringerOpen and Public Library of Science, while maintaining ties with European research funding bodies including European Research Council and Horizon 2020-funded projects.

Scope and Topics

The journal covers algorithmic, experimental, and theoretical contributions related to audio, speech, and music, intersecting with technologies developed at Bell Labs, Fraunhofer Society, Sony CSL, Google Research, and Microsoft Research. Topic areas include but are not limited to audio source separation as studied by teams at Queen Mary University of London and University of Illinois Urbana–Champaign, speech enhancement linked to work at Carnegie Mellon University and Johns Hopkins University, music information retrieval research from Queen Mary University of London and Cornell University, and perceptual evaluation methods influenced by groups at IRCAM and McGill University. Contributions often reference benchmark corpora and challenges hosted by LDC, TIMIT corpus, MIREX, CHiME Challenge, and datasets from Spotify Research and The Echo Nest.

Editorial Board and Publisher

The editorial board is composed of academics and industry scientists affiliated with institutions such as Imperial College London, University of Southern California, KTH Royal Institute of Technology, National University of Singapore, Duke University, University of Tokyo, and Peking University. Editorial practices reflect standards from editors who have also served on boards of IEEE Transactions on Pattern Analysis and Machine Intelligence and ACM Computing Surveys. The publisher operates in partnership with EURASIP and follows publishing frameworks comparable to MDPI and Wiley Online Library offerings while interacting with indexing services provided by Clarivate Analytics and Scopus.

Abstracting and Indexing

The journal is indexed in major bibliographic databases alongside titles like Nature Communications, Science Advances, and PLOS ONE, and is discoverable through services such as Scopus, Web of Science, Google Scholar, and CrossRef. It appears in thematic aggregations and citation analyses alongside works from Proceedings of the IEEE, NeurIPS, ICML, EMNLP, and ACL, facilitating cross-referencing with disciplines represented at Royal Society meetings and national academies such as the National Academy of Engineering.

Publication Model and Open Access

Adopting a gold open-access model, the journal’s articles are available immediately under publishing terms akin to Creative Commons licensing used by PLOS and BioMed Central. Article processing charges and waiver policies mirror practices seen at publishers like Springer Nature and IEEE Xplore open-access programs, and funding acknowledgements commonly cite agencies such as NSF, European Research Council, Engineering and Physical Sciences Research Council, and national research councils including DFG and ANR.

Notable Articles and Impact

Notable contributions have advanced methods in blind source separation inspired by work from Y. Huang-affiliated groups, deep learning approaches paralleling breakthroughs at Google DeepMind and Facebook AI Research, and evaluation frameworks that build on standards set by ITU and perceptual protocols used by AES task forces. Articles published in the journal have been cited alongside influential papers in IEEE Transactions on Neural Networks and Learning Systems, Journal of Machine Learning Research, and proceedings from ICASSP and NeurIPS, shaping research agendas at laboratories such as SRI International, NVIDIA Research, and Yahoo! Research.

Conferences and Special Issues

The journal frequently organizes special issues linked to conferences and workshops including ICASSP, INTERSPEECH, ISMIR, AES Convention, and symposia at institutions like CNRS and Max Planck Society. Guest-edited issues have reflected themes from EU-funded projects and collaborations with industry partners such as Dolby Laboratories, NVIDIA, Apple Inc., Amazon, and Tencent.

Category:Academic journals