logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Audio Source Separation 1st Edition Shoji Makino Eds

  • SKU: BELL-6989626
Audio Source Separation 1st Edition Shoji Makino Eds
$ 31.00 $ 45.00 (-31%)

4.3

18 reviews

Audio Source Separation 1st Edition Shoji Makino Eds instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 14.84 MB
Author: Shoji Makino (eds.)
ISBN: 9783319730301, 9783319730318, 3319730304, 3319730312
Language: English
Year: 2018
Edition: 1

Product desciption

Audio Source Separation 1st Edition Shoji Makino Eds by Shoji Makino (eds.) 9783319730301, 9783319730318, 3319730304, 3319730312 instant download after payment.

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.

Related Products