Connectionists: Special Issue Machine Learning for Audio in IEEE JSTSP

[Purwins, Hendrik]

Dear List,

we are excited to announce the publication of the Special Issue on  Machine Learning for Audio Signal Processing  in the IEEE Journal of Selected Topics in Signal Processing:
https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=8717740<https://urldefense.proofpoint.com/v2/url?u=https-3A__ieeexplore.ieee.org_xpl_tocresult.jsp-3Fisnumber-3D8717740&d=DwMDaQ&c=eIGjsITfXP_y-DLLX0uEHXJvU8nOHrUK8IrwNKOtkVU&r=lOEgrDKEbRAlb5JlCz9yfDJanx0zF9062jeI728awOg&m=nqCwxNARvuK_PRe5KODNUzPJ890Ce9rn_zqgi40iiNQ&s=QCY7s-SR2MUey8z_EVKeb5AZmmU8F2Od-9iEBP_Yt34&e=>

Audio signal processing is currently undergoing a paradigm change, where data-driven machine learning is replacing hand-crafted feature design. This issue is focused on machine learning techniques in the area of sound, speech and music signal processing, as well as methodological considerations of merging machine learning with audio signal processing. Various topics are covered, from a review of deep learning in the audio domain (Purwins et al.) to speech recognition (Bavu et al.), from voice activity detection (Ariav and Cohen) to musical brain state decoding (Ntalampiras and Potamitis), from music information retrieval (Kim et al.) to bioacoustic classification for species monitoring (Thakur and Rajan), from polyphonic acoustic event detection (Vesperini et al.) to heart sound segmentation (Oliveira et al.) and from speech enhancement (Wood and Rouat) to source separation (Le Roux et al.).

We hope you will find this special issue useful!

Best,
Hendrik Purwins, Bob Sturm, Bo Li, Juhan Nam, Abeer Alwan
Dr. Hendrik Purwins
Senior Manager & AI Lead  Emerging Technologies & Growth, ASGR
Accenture


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