Speech Enhancement: A Signal Subspace Perspective (Paperback)

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.

• First short book treating subspace approaches in a unified way for time and frequency domains, single-channel, multichannel, as well as binaural, speech enhancement.
• Bridges the gap between optimal filtering methods and subspace approaches.
• Includes original presentation of subspace methods from different perspectives.

語音增強是信號處理中的一個經典問題，但仍然在很大程度上尚未解決。解決這個問題的兩種常規方法是線性濾波，如經典的Wiener濾波器，和子空間方法。這些方法傳統上被視為不同類別的方法，並且在不同的背景下引入。線性濾波方法源於隨機過程，而子空間方法主要基於數值線性代數和矩陣逼近理論的發展。

本書通過展示如何將子空間方法的思想融入傳統的線性濾波中，彌合了這兩類方法之間的差距。在子空間方法的背景下，增強問題可以被視為一個經典的線性濾波器設計問題。這意味著各種解決方案可以更容易地進行比較，並且可以根據降噪和語音失真的性能進行界定和評估。本書展示了如何在這個框架中獲得各種濾波器設計，包括最大信噪比、Wiener、LCMV和MVDR濾波器，以及如何應用於單通道和多通道語音增強以及時間和頻率域。

本書的特點包括：
- 首本以統一方式處理時間和頻率域、單通道、多通道以及雙耳語音增強的短書。
- 彌合了最優濾波方法和子空間方法之間的差距。
- 包括從不同角度對子空間方法進行原創性介紹。