Recent Advances in Audio, Speech and Music Processing and Analysis, 2nd Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 2516

Special Issue Editors


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Guest Editor
Department of Music Technology & Acoustics, Hellenic Mediterranean University, 74133 Rethymnon, Greece
Interests: networked music performance; machine musicianship; music information retrieval; musical acoustics
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Special Issue Information

Dear Colleagues,

Audio plays an important role in everyday life since it is incorporated in various applications from broadcasting and telecommunications to the entertainment, multimedia, and gaming industries. Although less popular than image processing technology, which has overwhelmed the industry in recent years, audio processing in academia is under vigorous research and technological development. The relevant research initiatives are involved with speech recognition, audio compression, noise canceling, speaker verification and identification, voice synthesis, and voice transcription systems, to name a few. Furthermore, with respect to music signals, research initiatives focus on music information retrieval for music streaming and recommendation, networked music making, teaching and performing, autonomous and semi-autonomous computer musicians, and many more. This Special Issue gives the opportunity to disseminate state-of-the-art progress on emerging applications, algorithms, and systems related to audio, speech, and music processing and analysis.

Topics of interest include but are not limited to the following:

  • Audio and speech analysis and recognition;
  • Deep learning for robust speech recognition systems;
  • Active noise canceling systems;
  • Blind speech separation;
  • Robust speech recognition in multi-simultaneous speaker environments;
  • Room acoustics modeling;
  • Dereverberation;
  • Environmental sound recognition;
  • Music information retrieval;
  • Networked music performance systems;
  • Technologies and applications of internet of sounds;
  • Computer accompaniment and machine musicianship;
  • Digital music representations and collaborative music making;
  • Online music education technologies;
  • Computational approaches to musical acoustics;
  • Music generation using deep learning.

We look forward to your valuable contributions.

Dr. Athanasios Koutras
Dr. Chrisoula Alexandraki
Guest Editors

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Keywords

  • sound analysis
  • sound processing
  • music information retrieval
  • audio analysis
  • audio recognition
  • music technology
  • computational music cognition

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Published Papers (1 paper)

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Research

21 pages, 4948 KiB  
Article
Simultaneous Localization of Two Talkers Placed in an Area Surrounded by Asynchronous Six-Microphone Arrays
by Toru Takahashi, Taiki Kanbayashi and Masato Nakayama
Electronics 2025, 14(4), 711; https://doi.org/10.3390/electronics14040711 - 12 Feb 2025
Viewed by 2367
Abstract
If we can understand dialogue activities, it will be possible to know the role of each person in the discussion, and it will be possible to provide basic materials for formulating facilitation strategies. This understanding can be expected to be used for business [...] Read more.
If we can understand dialogue activities, it will be possible to know the role of each person in the discussion, and it will be possible to provide basic materials for formulating facilitation strategies. This understanding can be expected to be used for business negotiations, group work, active learning, etc. To develop a system that can monitor speech activity over a wide range of areas, we propose a method for detecting multiple acoustic events and localizing sound sources using an asynchronous distributed microphone array arranged in a regular hexagonal repeating structure. In contrast to conventional methods based on sound source direction using triangulation with microphone arrays, we propose a method for detecting acoustic events and determining sound sources from local maximum positions based on estimation of the spatial energy distribution inside the observation space. We evaluated the conventional method and the proposed method in an experimental environment in which a dialogue between two people was simulated under 22,104 conditions by using the sound source signal convolving the measured impulse response.We found that the performance changes depending on the selection of the microphone array used for estimation. Our finding is that it is best to choose five microphone arrays close to the evaluation position. Full article
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