By Jacob Benesty, Jingdong Chen

Though noise aid and speech enhancement difficulties were studied for no less than 5 many years, advances in our knowing and the improvement of trustworthy algorithms are extra vital than ever, as they aid the layout of adapted strategies for essentially outlined functions. during this paintings, the authors suggest a conceptual framework that may be utilized to the various various points of noise aid, supplying a uniform procedure

to monaural and binaural noise aid difficulties, within the time area and within the frequency area, and related to a unmarried or a number of microphones. in addition, the derivation of optimum filters is simplified, as are the functionality measures used for his or her evaluation.

**Read Online or Download A Conceptual Framework for Noise Reduction PDF**

**Similar & telecommunications books**

**Parallel Finite-Difference Time-Domain Method**

The finite-difference time-domain (FTDT) procedure has revolutionized antenna layout and electromagnetics engineering. This ebook increases the FDTD strategy to the following point via empowering it with the mammoth services of parallel computing. It indicates engineers the right way to make the most the traditional parallel houses of FDTD to enhance the present FDTD process and to successfully clear up extra complicated and big challenge units.

**Modulation, Detection and Coding**

Telecommunications represent an more and more vital a part of human society. In many ways, they're a starting place on which business international locations depend. Telecommunications play in several parts together with, banking, air site visitors keep watch over, drugs, electronic and voice communications. a growing number of humans have to comprehend the rules of contemporary telecommunications.

**Safety Management for Software-based Equipment**

Content material: bankruptcy 1 safeguard administration (pages 1–8): Jean? Louis BoulangerChapter 2 From process to software program (pages 9–17): Jean? Louis BoulangerChapter three Certifiable structures (pages 19–42): Jean? Louis BoulangerChapter four hazard and security degrees (pages 43–78): Jean? Louis BoulangerChapter five rules of protection (pages 79–120): Jean?

- Building a Geodatabase: ArcGIS 9
- Globalization, Uncertainty and Late Careers in Society (Routledge Advances in Sociology)
- Introductory Non-Euclidean Geometry
- La Santa Muerte: Unearthing the Magic & Mysticism of Death
- Clinical manual of geriatric psychiatry
- Universes without us : posthuman cosmologies in American literature

**Additional info for A Conceptual Framework for Noise Reduction**

**Sample text**

In this chapter, we approach this problem with the widely linear theory in the time domain, where both the temporal and spatial information is exploited. 1 Signal Model In this study, we consider the signal model in which 2M microphones1 capture a source signal convolved with acoustic impulse responses in some noise ﬁeld. The signal received at the ith microphone is then expressed as yr,i (t) = gi (t) ∗ s(t) + vr,i (t) = xr,i (t) + vr,i (t), i = 1, 2, . . 1) where gi (t) is the acoustic impulse response from the unknown speech source, s(t), location to the ith microphone, ∗ stands for linear convolution, and vr,i (t) is the additive noise at microphone i.

27) is the residual interference. We observe that the estimate of the desired signal at time t is the sum of three terms that are mutually uncorrelated. 31) Φxd = φx1 ρxx1 ρH xx1 is the correlation matrix (whose rank is equal to 1) H of xd (t), and Φxi = E xi (t)xH i (t) , Φx = E x(t)x (t) , and Φv = E v(t)vH (t) are the correlation matrices of xi (t), x(t), and v(t), respectively. 25) that the objective of our noise reduction problem is to ﬁnd optimal ﬁlters that can minimize the eﬀect of xri (t) + vrn (t) while preserving the desired signal, x1 (t).

Therefore, we deﬁne the subband and fullband speech quality indices as 38 4 Single-Channel Noise Reduction in the STFT Domain φVrn (k, n) φV (k, n) hH (k, n)Φv (k, n)h(k, n) , k = 0, 1, . . 48) and υq [h(:, n)] = = = K−1 k=0 φVrn (k, n) K−1 k=0 φV (k, n) K−1 H k=0 h (k, n)Φv (k, n)h(k, n) K−1 k=0 φV (k, n) K−1 k=0 φV (k, n)υq [h(k, n)] . 49) The speech quality indices are also expected to be upper bounded by 1 for optimal ﬁlters. Low values of the speech quality indices imply a good signal quality.