Proceedings ArticleDOI
Speech enhancement based on a priori signal to noise estimation
Pascal Scalart,J.V. Filho +1 more
- Vol. 2, pp 629-632
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TLDR
A new approach is then developed which achieves a trade-off between effective noise reduction and low computational load for real-time operations and demonstrates that the subjective and objective results are much better than existing methods.Abstract:
This paper addresses the problem of single microphone frequency domain speech enhancement in noisy environments. The main characteristics of available frequency domain noise reduction algorithms are presented. We have confirmed that the a priori SNR estimation leads to the best subjective results. According to these conclusions, a new approach is then developed which achieves a trade-off between effective noise reduction and low computational load for real-time operations. The obtained solutions demonstrate that the subjective and objective results are much better than existing methods.read more
Citations
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Journal ArticleDOI
A regression approach to speech enhancement based on deep neural networks
TL;DR: The proposed DNN approach can well suppress highly nonstationary noise, which is tough to handle in general, and is effective in dealing with noisy speech data recorded in real-world scenarios without the generation of the annoying musical artifact commonly observed in conventional enhancement methods.
Proceedings ArticleDOI
SEGAN: Speech Enhancement Generative Adversarial Network
TL;DR: This work proposes the use of generative adversarial networks for speech enhancement, and operates at the waveform level, training the model end-to-end, and incorporate 28 speakers and 40 different noise conditions into the same model, such that model parameters are shared across them.
Journal ArticleDOI
Subjective comparison and evaluation of speech enhancement algorithms
Yi Hu,Philipos C. Loizou +1 more
TL;DR: A noisy speech corpus is developed suitable for evaluation of speech enhancement algorithms encompassing four classes of algorithms: spectral subtractive, subspace, statistical-model based and Wiener-type algorithms.
Journal ArticleDOI
Speech enhancement for non-stationary noise environments
Israel Cohen,Baruch Berdugo +1 more
TL;DR: An optimally-modi#ed log-spectral amplitude (OM-LSA) speech estimator and a minima controlled recursive averaging (MCRA) noise estimation approach for robust speech enhancement are presented.
Journal ArticleDOI
Unbiased MMSE-Based Noise Power Estimation With Low Complexity and Low Tracking Delay
TL;DR: It is shown that the proposed speech presence probability (SPP) approach maintains the quick noise tracking performance of the bias compensated minimum mean-square error (MMSE)-based approach while exhibiting less overestimation of the spectral noise power and an even lower computational complexity.
References
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Journal ArticleDOI
Suppression of acoustic noise in speech using spectral subtraction
TL;DR: A stand-alone noise suppression algorithm that resynthesizes a speech waveform and can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
Journal ArticleDOI
Enhancement and bandwidth compression of noisy speech
Jae Lim,Alan V. Oppenheim +1 more
TL;DR: An overview of the variety of techniques that have been proposed for enhancement and bandwidth compression of speech degraded by additive background noise is provided to suggest a unifying framework in terms of which the relationships between these systems is more visible and which hopefully provides a structure which will suggest fruitful directions for further research.
Journal ArticleDOI
Speech enhancement using a soft-decision noise suppression filter
R. McAulay,M. Malpass +1 more
TL;DR: In this paper, a spectral decomposition of a frame of noisy speech is used to attenuate a particular spectral line depending on how much the measured speech plus noise power exceeds an estimate of the background noise.
Journal ArticleDOI
Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor
TL;DR: A study of the noise suppression technique proposed by Ephraim and Malah (1984,1985) and it is demonstrated how this artifact is actually eliminated without bringing distortion to the recorded signal even if the noise is only poorly stationary.
Proceedings ArticleDOI
Optimal estimators for spectral restoration of noisy speech
J. Porter,S. Boll +1 more
TL;DR: Results for a speaker dependent connected digit speech recognition task with a base error rate of 1.6%, show that preprocessing the noisy unknown speech with a 10 dB signal-to-noise ratio reduces the error rate from 42% to 10%.