Skip to main content
SpringerLink
Log in
Book cover

Blind Speech Separation

  • Book
  • © 2007

Overview

Editors:
  1. Shoji Makino

    1. NTT Corporation, Soraku-gun, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Hiroshi Sawada

    1. NTT Corporation, Soraku-gun, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Te-Won Lee

    1. University of California, San Diego, La Jolla, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • cutting edge topic on blind source separation
  • top researchers from all over the world
  • tutorial in nature and in-depth treatment

Part of the book series: Signals and Communication Technology (SCT)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (15 chapters)

  1. Front Matter

    Pages I-XV
    Download chapter PDF

  2. Multiple Microphone Blind Speech Separation with ICA

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Convolutive Blind Source Separation for Audio Signals

      • Scott C. Douglas, Malay Gupta
      Pages 3-45

    3. Frequency-Domain Blind Source Separation

      • Shoji Makino, Hiroshi Sawada, Shoko Araki
      Pages 47-78

    4. Blind Source Separation using Space–Time Independent Component Analysis

      • Mike Davies, Maria Jafari, Samer Abdallah, Emmanuel Vincent, Mark Plumbley
      Pages 79-99

    5. TRINICON-based Blind System Identification with Application to Multiple-Source Localization and Separation

      • Herbert Buchner, Robert Aichner, Walter Kellermann
      Pages 101-147

    6. SIMO-Model-Based Blind Source Separation – Principle and its Applications

      • Hiroshi Saruwatari, Tomoya Takatani, Kiyohiro Shikano
      Pages 149-168

    7. Independent Vector Analysis for Convolutive Blind Speech Separation

      • Intae Lee, Taesu Kim, Te-Won Lee
      Pages 169-192

    8. Relative Newton and Smoothing Multiplier Optimization Methods for Blind Source Separation

      • Michael Zibulevsky
      Pages 193-214

  3. Underdetermined Blind Speech Separation with Sparseness

    1. Front Matter

      Pages 215-215
      Download chapter PDF

    2. The DUET Blind Source Separation Algorithm

      • Scott Rickard
      Pages 217-241

    3. K-means Based Underdetermined Blind Speech Separation

      • Shoko Araki, Hiroshi Sawada, Shoji Makino
      Pages 243-270

    4. Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and L1-Norm Minimization

      • Stefan Winter, Walter Kellermann, Hiroshi Sawada, Shoji Makino
      Pages 271-304

    5. Bayesian Audio Source Separation

      • Cédric Févotte
      Pages 305-335

  4. Single Microphone Blind Speech Separation

    1. Front Matter

      Pages 337-337
      Download chapter PDF

    2. Monaural Source Separation

      • Gil-Jin Jang, Te-Won Lee
      Pages 339-364

    3. Probabilistic Decompositions of Spectra for Sound Separation

      • Paris Smaragdis
      Pages 365-386

    4. Sparsification for Monaural Source Separation

      • Hiroki Asari, Rasmus K. Olsson, Barak A. Pearlmutter, Anthony M. Zador
      Pages 387-410

    5. Monaural Speech Separation by Support Vector Machines: Bridging the Divide Between Supervised and Unsupervised Learning Methods

      • Sepp Hochreiter, Michael C. Mozer
      Pages 411-428

  5. Back Matter

    Pages 429-432
    Download chapter PDF
Back to top

Keywords

About this book

We are surrounded by sounds. Such a noisy environment makes it di?cult to obtain desired speech and it is di?cult to converse comfortably there. This makes it important to be able to separate and extract a target speech signal from noisy observations for both man–machine and human–human communication. Blindsourceseparation(BSS)isanapproachforestimatingsourcesignals using only information about their mixtures observed in each input channel. The estimation is performed without possessing information on each source, such as its frequency characteristics and location, or on how the sources are mixed. The use of BSS in the development of comfortable acoustic com- nication channels between humans and machines is widely accepted. Some books have been published on BSS, independent component ana- sis (ICA), and related subjects. There, ICA-based BSS has been well studied in the statistics and information theory ?elds, for applications to a variety of disciplines including wireless communication and biomedicine. However, as speech and audio signal mixtures in a real reverberant environment are generally convolutive mixtures, they involve a structurally much more ch- lenging task than instantaneous mixtures, which are prevalent in many other applications.

Editors and Affiliations

  • NTT Corporation, Soraku-gun, Japan

    Shoji Makino, Hiroshi Sawada

  • University of California, San Diego, La Jolla, USA

    Te-Won Lee

About the editors

Dr. Shoji Makino is an IEEE Fellow, Associate Editor of the IEEE Transactions on Speech & Audio Processing, and Executive Manager NTT Communication Science Laboratories. Dr. Makino was also co-editor on the succesful 2005 Springer book: Benesty - Speech Enhancement.

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation