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Titlebook: A Perspective on Single-Channel Frequency-Domain Speech Enhancement; Jacob Benesty,Yiteng Huang Book 2011 Springer Nature Switzerland AG 2

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發(fā)表于 2025-3-21 19:36:37 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱A Perspective on Single-Channel Frequency-Domain Speech Enhancement
影響因子2023Jacob Benesty,Yiteng Huang
視頻videohttp://file.papertrans.cn/142/141668/141668.mp4
學(xué)科分類Synthesis Lectures on Speech and Audio Processing
圖書封面Titlebook: A Perspective on Single-Channel Frequency-Domain Speech Enhancement;  Jacob Benesty,Yiteng Huang Book 2011 Springer Nature Switzerland AG 2
影響因子This book focuses on a class of single-channel noise reduction methods that are performed in the frequency domain via the short-time Fourier transform (STFT). The simplicity and relative effectiveness of this class of approaches make them the dominant choice in practical systems. Even though many popular algorithms have been proposed through more than four decades of continuous research, there are a number of critical areas where our understanding and capabilities still remain quite rudimentary, especially with respect to the relationship between noise reduction and speech distortion. All existing frequency-domain algorithms, no matter how they are developed, have one feature in common: the solution is eventually expressed as a gain function applied to the STFT of the noisy signal only in the current frame. As a result, the narrowband signal-to-noise ratio (SNR) cannot be improved, and any gains achieved in noise reduction on the fullband basis come with a price to pay, which is speechdistortion. In this book, we present a new perspective on the problem by exploiting the difference between speech and typical noise in circularity and interframe self-correlation, which were ignored i
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B. Hague D.SC., PH.D., F.C.G.I.used. We can divide these performance measures into two categories. The first category evaluates the noise reduction performance while the second one evaluates speech distortion. We also discuss the very convenient mean-square error (MSE) criterion and show how it is related to the performance measu
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An Introduction to Vegetation Analysis algorithms such as the MVDR, which is not possible with the classical method (i.e., Model 1). This new perspective is extremely important not only from a theoretical point of view but also from a practical point of view.
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Visualization in the Real World,number of the discussed algorithms, only the most typical and the most promising filters are investigated. The rest will be left to the reader for further exploration. Since we already learned from analytical analyzes presented in Chapter 6 that the gain in SNR from exploiting the circularity charac
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B. Hague D.SC., PH.D., F.C.G.I.In this chapter, we formulate the problem of the additive noise picked up by a single microphone along with the desired signal (speech) in the time and frequency domains. We also propose a general framework for studying the frequency-domain speech enhancement problem.
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