1. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
Adaptive Noise Estimation Algorithm for Speech Enhancement
Institute of Electrical and Electronics Engineering
Abstract:
A fast and robust speech noise estimation technique is proposed. The noisy speech is composed using a
critical-band-rate filter bank so that a perceptual modification of Wiener filtering can be applied in
speech denoising. The sub-band noise estimate is updated adaptively using a smoothing parameter that
depends on the estimated signal-to-noise ratio (SNR). This noise estimation technique can give accurate
results even at very low signal-to noise ratios. Speech denoising using perceptually modified Wiener
filtering combined with the proposed noise estimation technique gives enhanced speech of good
quality.

2. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
A: -
(a) Basic Overview of Additive Noise
(b) Basic Overview of Speech Enhancement System
(c) Overview of Spectral Subtraction System

3. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
(d) Two Channel Speech Enhancement
(e) Voice Activity Detection
(f) Block Diagram of Subspace Speech Enhancement System
(g) Block Diagram of Complete Subspace Speech Enhancement with Adaptive Noise Estimation
Algorithm

4. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
(h) Block Diagram of PESQ Algorithm

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B: - Waveforms
(a) Original wave, (b) Noisy (Corrupted) wave, and (c) Enhanced wave.
C: - Spectrograms
Spectrogram of (a) Original wave, (b) Noisy (Corrupted) wave, and (c) Enhanced wave.

6. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
Conclusion:
This thesis has focused on the design, implementation and testing of an adaptive noise estimation
algorithm for signal subspace speech enhancement. This is a novel approach to the subspace method [5]
which traditionally uses voice activity detection to estimate the noise in a signal. The proposed method
requires no voice activity detection and thus can update the noise estimate throughout the signal instead
of being limited to silence intervals. This allows a more accurate noise estimate to be produced and
improves the quality of the enhanced speech.
Objective and subjective tests were carried out to evaluate the success of the proposed algorithm. The
results were compared with those of contemporary speech enhancement systems and were shown to
outperform these systems for the majority of situations. The proposed algorithm was shown to produce
good quality speech in most noise types even at low signal to noise ratios. The proposed system has
potential applications in cellular telephony, audio archive restoration and automatic speech recognition.
All of these applications are heavily reliant on accurate and robust noise estimation to provide high quality
enhanced speech. Thus the proposed method is an ideal speech enhancement algorithm for these
situations.
Future Work:
Recent developments is subspace based speech enhancement, such as Klein and Kabal’s perceptual post
filter [22], and the work of Jabloun and Champagne in [34] have involved the exploitation of auditory
masking properties. The algorithm in this paper does not make use of these properties but they could be
incorporated relatively easily. This could potentially result in a further increase in system performance.
The subspace method is also rather computationally complex. Future work should also focus on the
reduction of this complexity. The discrete cosine transform was been proposed as an alternative to the
computationally complex KLT transform, and single value decomposition is another option for reducing
complexity. This will be significant as speech enhancement algorithms require in real-time implementation
for some applications, with more efficient algorithms allowing less power consumption and processor
usage.

7. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
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8. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
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9. Base paper: - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1199987
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[33] Opticom website PESQ description: http://www.opticom.de/technology/pesq.html
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Approach for Speech Enhancement,” IEEE Transactions on Speech and Audio Processing, vol. 11, No.6,
Nov 2003