Reprint
New Advances in Audio Signal Processing
Edited by
May 2024
206 pages
- ISBN978-3-7258-1059-8 (Hardback)
- ISBN978-3-7258-1060-4 (PDF)
This book is a reprint of the Special Issue New Advances in Audio Signal Processing that was published in
Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
In the era of digitalization, audio signal processing is gaining peculiar relevance as an automation and remote analysis means, also considering its enhancement by novel artificial intelligence (AI) techniques.
This Reprint aims to offer an overview of the current developments in all fields that revolve around audio processing: from advancements in the acoustic domain to deep learning architectures for the audio-based analysis of real-world problems such as pitch detection or pathology identification.
Format
- Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
fire protection equipment; acoustic nozzle; inert gas; halocarbon compound; sound pressure level; AI diagnostics; COVID-19 screening; deep learning; speech recognition; room reverberation; room impulse response; recurrent neural networks; audio signal spectrum; filter bank; sound quality; annoyance; perception; psychoacoustics; vacuum cleaner noise; household appliance noise; sound event detection; U-Net; weakly supervised learning; pooling; convolutional neural network; dolphin whistle; ensemble; spectrogram classification; pitch detection; F0; algorithm; auto-tune; audio signal processing; acoustic imaging; microphone arrays; robust super directive beamforming; array processing; miniaturization; aperiodic sparse planar arrays; filter-and-sum beamforming; data-independent 3-D digital beamforming; low-cost acoustic camera; sensor mismatches; personal audio system; sound field control; acoustic contrast; reconstruction error; array effort; automatic construction site monitoring (ACSM); environmental sound classification (ESC); deep learning; convolutional neural network (CNN); continuous wavelet transform (CWT); scalogram; audio processing