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Journal ArticleDOI

A perceptually motivated approach for speech enhancement

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TLDR
A new perceptually motivated approach is proposed for enhancement of speech corrupted by colored noise that takes into account the frequency masking properties of the human auditory system and reduces the perceptual effect of the residual noise.
Abstract
A new perceptually motivated approach is proposed for enhancement of speech corrupted by colored noise. The proposed approach takes into account the frequency masking properties of the human auditory system and reduces the perceptual effect of the residual noise. This new perceptual method is incorporated into a frequency-domain speech enhancement method and a subspace-based speech enhancement method. A better power spectrum/autocorrelation function estimator was also developed to improve the performance of the proposed algorithms. Objective measures and informal listening tests demonstrated significant improvements over other methods when tested with TIMIT sentences corrupted by various types of colored noise.

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Citations
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Journal ArticleDOI

Speech enhancement based on wavelet thresholding the multitaper spectrum

TL;DR: A short-time spectral amplitude estimator is derived which incorporates the wavelet-thresholded multitaper spectra for speech enhancement and showed that the use of multitaper spectrum estimation combined with wavelet thresholding suppressed the musical noise and yielded better quality than the subspace and MMSE algorithms.
Book

DFT-Domain Based Single-Microphone Noise Reduction for Speech Enhancement: A Survey of the State of the Art

TL;DR: This survey wishes to demonstrate the significant advances that have been made during the last decade in the field of discrete Fourier transform domain-based single-channel noise reduction for speech enhancement.
Journal ArticleDOI

A review of signal subspace speech enhancement and its application to noise robust speech recognition

TL;DR: An extensive overview of the available estimators is presented, and a theoretical estimator is derived to experimentally assess an upper bound to the performance that can be achieved by any subspace-based method.
Book

Speech Enhancement in the STFT Domain

TL;DR: This work addresses the problem of multichannel noise reduction in the STFT domain with and without interframe correlation and proposes different optimization cost functions from which the optimal filters are derived.
Journal ArticleDOI

Recent Developments in Speech Enhancement in the Short-Time Fourier Transform Domain

TL;DR: An overview of the conventional literature in the single- and multichannel cases of noise reduction in the short-time Fourier transform (STFT) domain and a detailed survey of the most recent advances in the STFT-based noise reduction methods are provided.
References
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Book

The Theory of Matrices

TL;DR: In this article, the Routh-Hurwitz problem of singular pencils of matrices has been studied in the context of systems of linear differential equations with variable coefficients, and its applications to the analysis of complex matrices have been discussed.
Book

Theory of matrices

Journal ArticleDOI

Spectrum estimation and harmonic analysis

TL;DR: In this article, a local eigenexpansion is proposed to estimate the spectrum of a stationary time series from a finite sample of the process, which is equivalent to using the weishted average of a series of direct-spectrum estimates based on orthogonal data windows to treat both bias and smoothing problems.
Book

Discrete-Time Processing of Speech Signals

TL;DR: The preface to the IEEE Edition explains the background to speech production, coding, and quality assessment and introduces the Hidden Markov Model, the Artificial Neural Network, and Speech Enhancement.
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