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In this paper, for enhancement of noisy speech, a method based on decision-directed Wiener approach in perceptual wavelet packet (PWP) domain is presented. The proposed method assumes an additive Gaussian noise model to derive the formulation of estimating the clean speech coefficients. The proposed method also considers the signal to noise ratio (SNR) information of the previous frame to obtain the...
In this work, we present a low-complexity single-ended objective intelligibility measure for noisy speech based on statistics computed from auditory modulation features. The proposed measure is obtained in two steps. First, we compute several statistics of auditory representation of corrupted speech. Next, a support vector regressor (SVR) is used to map these statistics to an overall intelligibility...
In this work, we are interested in assessing the optimality of the human auditory system, when the input stimuli is natural speech that is affected by additive noise. In order to do this, we consider the DANTALE II listening test paradigm of Wagener et al., which has been used to evaluate the intelligibility of noisy speech by exposing human listeners to a selection of constructed noisy sentences...
This paper is dedicated to the memory of Steven L. Grant for his exceptional contributions to the echo cancellation problem. The regularization is mandatory in all ill-posed problems, especially in the presence of additive noise. In this paper, we consider the regularized recursive least-squares (RLS) algorithm and present a method to find its regularization parameter, depending on the signal-to-noise...
State-of-the-art speaker recognition systems performance degrades considerably in noisy environments even though they achieve very good results in clean conditions. In order to deal with this strong limitation, we aim in this work to remove the noisy part of an i-vector directly in the i-vector space. Our approach offers the advantage to operate only at the i-vector extraction level, letting the other...
Filter banks proved to be effective in many signal processing contexts. A method to improve and to enlarge the set of filter banks applications consists in overcoming the effects of developing the perfect reconstruction condition without considering distortions inducted, inevitable, by quantization and transmission over additive noise disturbed channels. In this paper is presented an analysis filter...
The conventional linear prediction (LP) analysis is known to suffer from problems that it is sensitive to additive noise. In this paper a new approach for LP analysis of crosscorrelation sequence between speech signal and its zero-crossing wave has been presented. Simulation results show that the proposed method is capable of performing the speech analysis under a white noisy environment.
Different short-term spectrum estimators for speaker verification under additive noise are considered. Conventionally, mel-frequency cepstral coefficients (MFCCs) are computed from discrete Fourier transform (DFT) spectra of windowed speech frames. Recently, linear prediction (LP) and its temporally weighted variants have been substituted as the spectrum analysis method in speech and speaker recognition...
Considerable attention has been devoted to the reverberant blind source separation problem: in particular, the concept of time-frequency masking. However, realistic acoustic scenarios often comprise not only reverberation, but also additive noise due to factors such as non-ideal channels. This paper presents robust evaluations of a time-frequency masking approach for separation in such realistic conditions...
Many people have great difficulty in Understanding speech with background noise. Speech Enhancement plays a vital role in such situations. The background noise has to be removed from the noisy speech signal to increase the signal intelligibility and to reduce the listener fatigue. In this paper, a novel approach is used to enhance the perceived quality of the speech signal when the additive noise...
In this paper, an investigation to find a relationship between the send characteristics of VoIP phone and the speech recognition performance is presented. Experimental results under various additive noisy environments show that for improved speech recognition the send characteristics should be adjusted differently from the adjustment based on human perception. The better send characteristics for speech...
This paper addresses the problem of adaptive filtering for acoustic echo cancellation in noisy and non-linear environments. The first contribution relates to a new analysis on the comparative impact of additive noise and non-linear echo on the performance of adaptive filtering for linear acoustic echo cancellation (AEC). A comprehensive performance assessment is reported, including echo return loss...
The research on blind source separation is a focus in the community of signal processing and has been developed in recent years. In the current approaches, the additive noise is negligible so that it can be omitted from the consideration. To be applicable in realistic scenarios, blind source separation approaches should deal evenly with the presence of noise. In this contribution, we propose to independent...
The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a novel approach where a set of client-specific binary features carrying maximal discriminative information specific to the individual client are estimated from an ensemble of pair-wise comparisons of frequency components in magnitude...
This paper presents a novel data-driven technique for performing acoustic model adaptation to noisy environments. In the presence of additive noise, the relationship between log mel spectra of speech, noise and noisy speech is nonlinear. Traditional methods linearize this relationship using the mode of the nonlinearity or use some other approximation. The approach presented in this paper models this...
This paper examines the technique of using a memoryless noise-suppressing nonlinearity in the adaptive filter error feedback-loop of an acoustic echo canceler (AEC) based on normalized least-mean square (NLMS) when there is an additive noise at the near-end. It will be shown that introducing the nonlinearity to ldquoenhancerdquo the filter estimation error is well-founded in the information-theoretic...
This paper describes a method to increase speech intelligibility when the speech signal is being transmitted over telephone lines. In order to detect all factors which affect speech intelligibility, we use telephone simulation tool in ITUT Software Tools Library release 2005 (STL2005) to identify the most problematic telephone-channel deteriorations. Of the various effects considered, additive noise...
Blind SIMO identification is challenging when additive noise is strong and for ill-conditioned/acoustic SIMO systems. A weighted cross relation (CR) algorithm presumably can be robust to noise but there lacks a practical way to define the weights. In this paper, the Pearson correlation coefficient (PCC) is used to develop an optimally weighted CR algorithm, which is validated by simulations.
Mel-frequency cepstral coefficients (MFCC) are the most widely used features for speech recognition. However, MFCC-based speech recognition performance degrades in presence of additive noise. In this paper, we propose a set of noise-robust features based on conventional MFCC feature extraction method. Our proposed method consists of two steps. In the first step, mel sub-band Wiener filtering is carried...
The Mel-frequency cepstral coefficients (MFCC) are widely used for speech recognition. However, MFCC-based speech recognition performance degrades in presence of additive noise. In this paper, we propose a set of noise-robust features based on conventional MFCC feature extraction method. Our proposed method consists of two steps. In the first step, Mel sub-band spectral subtraction is carried out...
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