Skip to main content

Save up to 30% on Elsevier print and eBooks with free shipping. No promo code needed.

Save up to 30% on print and eBooks.

Speech Enhancement

A Signal Subspace Perspective

  • 1st Edition - January 4, 2014
  • Authors: Jacob Benesty, Jesper Rindom Jensen, Mads Graesboll Christensen, Jingdong Chen
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 1 2 - 8 0 0 1 3 9 - 4
  • eBook ISBN:
    9 7 8 - 0 - 1 2 - 8 0 0 2 5 3 - 7

Speech enhancement is a classical problem in signal processing, yet still largely unsolved. Two of the conventional approaches for solving this problem are linear filtering, li… Read more

Speech Enhancement

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Institutional subscription on ScienceDirect

Request a sales quote

Speech enhancement is a classical problem in signal processing, yet still largely unsolved. Two of the conventional approaches for solving this problem are linear filtering, like the classical Wiener filter, and subspace methods. These approaches have traditionally been treated as different classes of methods and have been introduced in somewhat different contexts. Linear filtering methods originate in stochastic processes, while subspace methods have largely been based on developments in numerical linear algebra and matrix approximation theory.

This book bridges the gap between these two classes of methods by showing how the ideas behind subspace methods can be incorporated into traditional linear filtering. In the context of subspace methods, the enhancement problem can then be seen as a classical linear filter design problem. This means that various solutions can more easily be compared and their performance bounded and assessed in terms of noise reduction and speech distortion. The book shows how various filter designs can be obtained in this framework, including the maximum SNR, Wiener, LCMV, and MVDR filters, and how these can be applied in various contexts, like in single-channel and multichannel speech enhancement, and in both the time and frequency domains.