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Books > Science & Mathematics > Physics > Classical mechanics > Sound, vibration & waves (acoustics)
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Audio Source Separation (Paperback, Softcover reprint of the original 1st ed. 2018)
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Audio Source Separation (Paperback, Softcover reprint of the original 1st ed. 2018)
Series: Signals and Communication Technology
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This book provides the first comprehensive overview of the
fascinating topic of audio source separation based on non-negative
matrix factorization, deep neural networks, and sparse component
analysis. The first section of the book covers single channel
source separation based on non-negative matrix factorization (NMF).
After an introduction to the technique, two further chapters
describe separation of known sources using non-negative spectrogram
factorization, and temporal NMF models. In section two, NMF methods
are extended to multi-channel source separation. Section three
introduces deep neural network (DNN) techniques, with chapters on
multichannel and single channel separation, and a further chapter
on DNN based mask estimation for monaural speech separation. In
section four, sparse component analysis (SCA) is discussed, with
chapters on source separation using audio directional statistics
modelling, multi-microphone MMSE-based techniques and diffusion map
methods. The book brings together leading researchers to provide
tutorial-like and in-depth treatments on major audio source
separation topics, with the objective of becoming the definitive
source for a comprehensive, authoritative, and accessible
treatment. This book is written for graduate students and
researchers who are interested in audio source separation
techniques based on NMF, DNN and SCA.
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