Showing papers on "Noise measurement published in 2002"

Noise Spectrum Estimation in Adverse Environments: Improved Minima Controlled

Abstract: Noise spectrum estimation is a fundamental component of speech enhancement and speech recognition systems. In this paper, we present an Improved Minima Con- trolled Recursive Averaging (IMCRA) approach, for noise es- timation in adverse environments involving non-stationary noise, weak speech components, and low input signal-to- noise ratio (SNR). The noise estimate is obtained by av- eraging past spectral power values, using a time-varying frequency-dependent smoothing parameter that is adjusted by the signal presence probability. The speech presence probability is controlled by the minima values of a smoothed periodogram. The proposed procedure comprises two iter- ations of smoothing and minimum tracking. The rst it- eration provides a rough voice activity detection in each frequency band. Then, smoothing in the second iteration excludes relatively strong speech components, which makes the minimum tracking during speech activity robust. We show that in non-stationary noise environments and under low SNR conditions, the IMCRA approach is very eectiv e. In particular, compared to a competitive method, it obtains a lower estimation error, and when integrated into a speech enhancement system achieves improved speech quality and lower residual noise.

Noise estimation by minima controlled recursive averaging for robust speech enhancement

Abstract: In this letter, we introduce a minima controlled recursive averaging (MCRA) approach for noise estimation. The noise estimate is given by averaging past spectral power values and using a smoothing parameter that is adjusted by the signal presence probability in subbands. The presence of speech in subbands is determined by the ratio between the local energy of the noisy speech and its minimum within a specified time window. The noise estimate is computationally efficient, robust with respect to the input signal-to-noise ratio (SNR) and type of underlying additive noise, and characterized by the ability to quickly follow abrupt changes in the noise spectrum.

A multi-band spectral subtraction method for enhancing speech corrupted by colored noise

Abstract: The spectral subtraction method is a well-known noise reduction technique. Most implementations and variations of the basic technique advocate subtraction of the noise spectrum estimate over the entire speech spectrum. However, real world noise is mostly colored and does not affect the speech signal uniformly over the entire spectrum. In this paper, we propose a multi-band spectral subtraction approach which takes into account the fact that colored noise affects the speech spectrum differently at various frequencies. This method outperforms the standard power spectral subtraction method resulting in superior speech quality and largely reduced musical noise.

Speech pause detection for noise spectrum estimation by tracking power envelope dynamics

Abstract: A speech pause detection algorithm is an important and sensitive part of most single-microphone noise reduction schemes for enhancement of speech signals corrupted by additive noise as an estimate of the background noise is usually determined when speech is absent. An algorithm is proposed which detects speech pauses by adaptively tracking minima in a noisy signal's power envelope both for the broadband signal and for the high-pass and low-pass filtered signal. In poor signal-to-noise ratios (SNRs), the proposed algorithm maintains a low false-alarm rate in the detection of speech pauses while the standardized algorithm of ITU G.729 shows an increasing false-alarm rate in unfavorable situations. These characteristics are found with different types of noise and indicate that the proposed algorithm is better suited to be used for noise estimation in noise reduction algorithms, as speech deterioration may thus be kept at a low level. It is shown that in connection with the Ephraim-Malah (1984) noise reduction scheme, the speech pause detection performance can even be further increased by using the noise-reduced signal instead of the noisy signal as input for the speech pause decision unit.

Acoustic Analogy and Alternative Theories for Jet Noise Prediction

Abstract: Several methods for the prediction of jet noise are described. All but one of the noise prediction schemes are based on Lighthill's or Lilley's acoustic analogy, whereas the other is the jet noise generation model recently proposed by Tam and Auriault. In all of the approaches, some assumptions must be made concerning the statistical properties of the turbulent sources. In each case the characteristic scales of the turbulence are obtained from a solution of the Reynolds-averaged Navier-Stokes equation using a kappa-sigma turbulence model. It is shown that, for the same level of empiricism, Tam and Auriault's model yields better agreement with experimental noise measurements than the acoustic analogy. It is then shown that this result is not because of some fundamental flaw in the acoustic analogy approach, but instead is associated with the assumptions made in the approximation of the turbulent source statistics. If consistent assumptions are made, both the acoustic analogy and Tam and Auriault's model yield identical noise predictions. In conclusion, a proposal is presented for an acoustic analogy that provides a clearer identification of the equivalent source mechanisms, as is a discussion of noise prediction issues that remain to be resolved.

Phase noise and timing jitter in oscillators with colored-noise sources

Abstract: Phase noise or timing jitter in oscillators is of major concern in wireless and optical communications, being a major contributor to the bit-error rate of communication systems, and creating synchronization problems in other clocked and sampled-data systems. This paper presents the theory and practical characterization of phase noise in oscillators due to colored, as opposed to white, noise sources. Shot and thermal noise sources in oscillators can be modeled as white-noise sources for all practical purposes. The characterization of phase noise in oscillators due to shot and thermal noise sources is covered by a recently developed theory of phase noise due to white-noise sources. The extension of this theory and the practical characterization techniques to noise sources in oscillators, which have a colored spectral density, e.g., 1/f noise, is crucial for practical applications. In this paper, we first derive a stochastic characterization of phase noise in oscillators due to colored-noise sources. This stochastic analysis is based on a novel nonlinear perturbation analysis for autonomous systems, and a nonlocal Fokker-Planck equation we derive. Then, we calculate the resulting spectrum of the oscillator output with phase noise as characterized. We also extend our results to the case when both white and colored-noise sources are present. Our treatment of phase noise due to colored-noise sources is general, i.e., it is not specific to a particular type of colored-noise source.

Classification image weights and internal noise level estimation.

Abstract: For the linear discrimination of two stimuli in white Gaussian noise in the presence of internal noise, a method is described for estimating linear classification weights from the sum of noise images segregated by stimulus and response. The recommended method for combining the two response images for the same stimulus is to difference the average images. Weights are derived for combining images over stimuli and observers. Methods for estimating the level of internal noise are described with emphasis on the case of repeated presentations of the same noise sample. Simple tests for particular hypotheses about the weights are shown based on observer agreement with a noiseless version of the hypothesis.

Noise suppression for a wireless communication device

Abstract: Techniques to suppress noise from a signal comprised of speech plus noise. In accordance with aspects of the invention, two or more signal detectors (e.g., microphones) are used to detect respective signals having speech and noise components, with the magnitude of each component being dependent on various factors such as the distance between the speech source and the microphone. Signal processing is then used to process the detected signals to generate the desired output signal having predominantly speech with a large portion of the noise removed. The techniques described herein may be advantageously used for both near-field and far-field applications, and may be implemented in various mobile communication devices such as cellular phones.

Uncertainty decoding with SPLICE for noise robust speech recognition

Abstract: Speech recognition front end noise removal algorithms have. in the past, estimated clean speech features from corrupted speech features. The accuracy of the noise removal process varies from frame to frame, and from dimension to dimension in the feature stream, due in part to the instantaneous SR of the input. In this paper, we show that localized knowledge of the accuracy of the noise removal process can be directly incorporated into the Gaussian evaluation within the decoder, to produce higher recognition accuracies. To prove this concept, we modify the SPLICE algorithm to output uncertainty information, and show that the combination of SPLICE with uncertainty decoding can remove 74.2% of the errors in a subset of the Aurora2 task.

A noise optimization technique for integrated low-noise amplifiers

Abstract: Based on measured four-noise parameters and two-port noise theory, considerations for noise optimization of integrated low-noise amplifier (LNA) designs are presented. If arbitrary values of source impedance are allowed, optimal noise performance of the LNA is obtained by adjusting the source degeneration inductance. Even for a fixed source impedance, the integrated LNA can achieve near NF/sub min/ by choosing an appropriate device geometry along with an optimal bias condition. An 800 MHz LNA has been implemented in a standard 0.24 /spl mu/m CMOS technology. The amplifier possesses a 0.9 dB noise figure with a 7.1 dBm third-order input intercept point, while drawing 7.5 mW from a 2.0 V power supply, demonstrating that the proposed methodology can accurately predict noise performance of integrated LNA designs.

A psychoacoustic approach to combined acoustic echo cancellation and noise reduction

Abstract: This paper presents and compares algorithms for combined acoustic echo cancellation and noise reduction for hands-free telephones. A structure is proposed, consisting of a conventional acoustic echo canceler and a frequency domain postfilter in the sending path of the hands-free system. The postfilter applies the spectral weighting technique and attenuates both the background noise and the residual echo which remains after imperfect echo cancellation. Two weighting rules for the postfilter are discussed. The first is a conventional one, known from noise reduction, which is extended to attenuate residual echo as well as noise. The second is a psychoacoustically motivated weighting rule. Both rules are evaluated and compared by instrumental and auditive tests. They succeed about equally well in attenuating the noise and the residual echo. In listening tests, however, the psychoacoustically motivated weighting rule is mostly preferred since it leads to more natural near end speech and to less annoying residual noise.

Weighted range sensor matching algorithms for mobile robot displacement estimation

Abstract: Introduces a "weighted" matching algorithm to estimate a robot's planar displacement by matching two-dimensional range scans. The influence of each scan point on the overall matching error is weighted according to its uncertainty. We develop uncertainty models that account for effects such as measurement noise, sensor incidence angle, and correspondence error. Based on models of expected sensor uncertainty, our algorithm computes the appropriate weighting for each measurement so as to optimally estimate the displacement between two consecutive poses. By explicitly modeling the various noise sources, we can also calculate the actual covariance of the displacement estimates instead of a statistical approximation of it. A realistic covariance estimate is necessary for further combining the pose displacement estimates with additional odometric and/or inertial measurements within a localization framework. Experiments using a Nomad 200 mobile robot and a Sick LMS-200 laser range finder illustrate that the method is more accurate than prior techniques.

Noise adaptive stream weighting in audio-visual speech recognition

Abstract: It has been shown that integration of acoustic and visual information especially in noisy conditions yields improved speech recognition results. This raises the question of how to weight the two modalities in different noise conditions. Throughout this paper we develop a weighting process adaptive to various background noise situations. In the presented recognition system, audio and video data are combined following a Separate Integration (SI) architecture. A hybrid Artificial Neural Network/Hidden Markov Model (ANN/HMM) system is used for the experiments. The neural networks were in all cases trained on clean data. Firstly, we evaluate the performance of different weighting schemes in a manually controlled recognition task with different types of noise. Next, we compare different criteria to estimate the reliability of the audio stream. Based on this, a mapping between the measurements and the free parameter of the fusion process is derived and its applicability is demonstrated. Finally, the possibilities and limitations of adaptive weighting are compared and discussed.

An integrated audio and active noise control headsets

Abstract: This paper presents an integrated approach in designing a noise reduction headset for the audio and communication applications. Conventional passive headsets give good attenuation of ambient noise in the upper frequency range, while most of these devices fail below 500 Hz. Unlike the feedforward method, the adaptive feedback active noise control technique provides a more accurate noise cancellation since the microphone is placed inside the ear-cup of the headset. Furthermore, the system uses single microphone per ear cup, thus produces a more compact, lower power consumption, cheaper solution, and ease of integration with existing audio and communication devices to form an integrated feedback active noise control headsets. Simulation results have been conducted to show that the integrated approach can remove the disturbing noise and at the same time, allow the desired speech or audio signal to pass through without cancellation.

Performance of handoff algorithm based on distance and RSSI measurements

Abstract: The performance of a proposed handoff algorithm based on both the distance of a mobile station to neighboring base stations and the relative signal strength measurements is evaluated. The algorithm performs handoff when the measured distance from the serving base station exceeds that from the candidate base station by a given threshold and if the measured signal strength of the adjacent base station exceeds that of the serving base station by a given hysteresis level. The average handoff delay and average number of handoffs are used as criteria for performance. Numerical results are presented to demonstrate the feasibility of the distance-based handoff algorithm, including results for an additional criterion based on relative signal strength. The proposed algorithm is compared with an algorithm based on absolute and relative signal strength measurements and with a solely distance-based algorithm. It is found that the proposed handoff algorithm performs well in a log-normal fading environment when the distance estimate error is modeled by wide-sense stationary additive white Gaussian noise.

Apparatus for and method of reducing interference in a communications receiver

Abstract: A novel and useful apparatus for and method of interference reduction in a communications receiver. The invention first finds the channel estimate (70) and the noise vector (74) from the receive signal. An interference detector (78) is then used to choose an appropriate compensation filter and select between adaptive and deterministic moving average models for noise prediction. After compensation filtering, a new channel estimate and noise vector is calculated. The new noise vector is used to determine noise whitening coefficients if the adaptive model is used. In the deterministic model case, the coefficients do not need to be calculated since they are already known, having been calculated a priori. The noise whitening coefficients are then used in an equalizer (58) such as a Viterbi algorithm based equalizer.

Classification and characterization of impulsive noise on indoor powerline used for data communications

Abstract: The performance of a link using the indoor power line network as a medium for communication strongly depends on the noise characteristics. Besides the background noise and the narrow band noise mainly due to broadcast transmitters, impulsive noise adversely affects the quality of service. This paper focuses on impulsive noise measurements, their statistical properties being the basis of a noise model for optimizing a transmission scheme.

Signal Processing Noise

Abstract: PROBABILITY AND STATISTICS Probability: Basic Concepts Random Variables Stochastic Processes Correlation Function Spectral Density Statistical Characteristics Conclusions References CLASSICAL AND MODERN APPROACHES TO SIGNAL DETECTION THEORY Gaussian Approach Markov Approach Bayes' Decision-Making Rule Unbiased and Invariant Decision-Making Rules Mini-Max Decision-Making Rule Sequential Signal Detection Signal Detection in Non-Gaussian Noise Non-Parametric Signal Detection Conclusions References MAIN CHARACTERISTICS OF MULTIPLICATIVE NOISE Classification of the Noise and Interference Sources of the Multiplicative Noise Classification and Main Properties of Multiplicative Noise Correlation Function and Energy Spectrum of Multiplicative Noise Generalized Statistical Model of Multiplicative Noise Conclusions References STATISTICAL CHARACTERISTICS OF SIGNALS UNDER THE STIMULUS OF MULTIPLICATIVE NOISE Deterministic and Quasideterministic Multiplicative Noise Stationary Fluctuating Multiplicative Noise Ensemble and Individual Realizations of the Signal Probability Distribution Density of the Signal in the Additive Gaussian Noise under the Stimulus of Multiplicative Noise Multivariate Probability Distribution Density of Instantaneous Values of the Signal under the Stimulus of Fluctuating Multiplicative Noise Conclusions References MAIN THEORETICAL PRINCIPLES OF THE GENERALIZED APPROACH TO SIGNAL PROCESSING UNDER THE STIMULUS OF MULTIPLICATIVE NOISE Basic Concepts Criticism Initial Premises Likelihood Ratio Engineering Interpretation Generalized Detector Distribution Law Conclusions References GENERALIZED APPROACH TO SIGNAL PROCESSING UNDER THE STIMULUS OF MULTIPLICATIVE NOISE AND LINEAR SYSTEMS Signal Characteristics at the Output of Linear System of the Generalized Detector under the Stimulus of Multiplicative Noise Signal Characteristics at the Generalized Detector Output under under the Stimulus of Multiplicative Noise Signal Noise Component for Some Types of Signals Signal Noise Component under the Stimulus of the Slow and Rapid Multiplicative Noise Signal Distribution Law under the Stimulus of Multiplicative Noise Conclusions References GENERALIZED APPROACH TO SIGNAL DETECTION IN THE PRESENCE OF MULTIPLICATIVE AND ADDITIVE GAUSSIAN NOISE Statistical Characteristics of Signals at the Output of the Generalized Detector Detection Performances of the Generalized Detector Known Correlation Function of the Multiplicative Noise One-Channel Generalized Detector Diversity Signal Detection Conclusions References SIGNAL PARAMETER MEASUREMENT PRECISION A Single Signal Parameter Measurement under a Combined Stimulus of Weak Multiplicative and Additive Gaussian Noise Simultaneous Measurement of Two Signal Parameters under a Combined Stimulus of Weak Multiplicative and Additive Gaussian Noise A Single Parameter Measurement under a Combined Stimulus of High Multiplicative and Additive Gaussian Noise Conclusions References SIGNAL RESOLUTION UNDER THE GENERALIZED APPROACH TO SIGNAL PROCESSING IN THE PRESENCE OF NOISE Estimation Criteria of Signal Resolution Signal Resolution by Woodward Criterion Statistical Criterion of Signal Resolution Conclusions References APPENDIX I: Delta Function APPENDIX II: Correlation Function and Energy Spectrum of Noise Modulation Function NOTATION INDEX INDEX

Robust weighted averaging [of biomedical signals]

Abstract: Signal averaging is often used to extract a useful signal embedded in noise. This method is especially useful for biomedical signals, where the spectra of the signal and noise significantly overlap. In this case, traditional filtering techniques introduce unacceptable signal distortion. In averaging methods, constancy of the noise power is usually assumed, but in reality noise features a variable power. In this case, it is more appropriate to use a weighted averaging. The main problem in this method is the estimation of the noise power in order to obtain the weight values. Additionally, biomedical signals often contain outliers. This requires robust averaging methods. This paper shows that signal averaging can be formulated as a problem of minimization of a criterion function. Based on this formulation new weighted averaging methods are introduced, including weighted averaging based on criterion function minimization (WACFM) and robust /spl epsi/-insensitive WACFM. Performances of these new methods are experimentally compared with the traditional averaging and other weighted averaging methods using electrocardiographic signal with the muscle noise, impulsive noise, and time-misalignment of cycles. Finally, an application to the late potentials extraction is shown.

An integrated audio and active noise control headset

Abstract: This paper presents an integrated approach in designing a noise reduction headset for audio and communication applications. Conventional passive headsets give good attenuation of ambient noise in the upper frequency range, while most of these devices fail below 500 Hz. Unlike the feedforward method, the adaptive feedback active noise control technique provides more accurate noise cancellation since the microphone is placed inside the ear-cup of the headset. Furthermore, the system uses a single microphone per ear cup, thus producing a more compact, lower power consumption, cheaper solution and ease of integration with existing audio and communication devices to form an integrated feedback active noise control headset. Simulation results have been conducted to show that the integrated approach can remove the disturbing noise and, at the same time, allow the desired speech or audio signal to pass through without cancellation.

Impulse generation with appropriate amplitude, length, inter-arrival, and spectral characteristics

Abstract: This paper proposes a suitable method for simulating impulses with appropriate amplitude, spectral, and inter-arrival characteristics. The statistics used to develop the parameters of this model are based on statistics derived from observations of impulse noise on the telephone networks of British Telecom (BT) and Deutsche Telekom (DT). This paper initially reviews the former DT approach to impulse noise generation for testing digital subscriber line systems, so called xDSL systems. Some problems are highlighted and an alternative technique is suggested that is capable of generating impulses with both appropriate amplitude an spectral characteristics.

Characterization and modeling of in-building power lines for high-speed data transmission

Abstract: This paper analyzes the characteristics of power lines in the Singapore residential network in order to develop a channel model suitable to simulate its behavior for high-speed data transmission. The channel model, which describes the transfer function and noise characteristics of typical in-building power line channels in a frequency band from 1 to 10 MHz, is developed and tested through software simulation and hardware implementation. The transfer function is described by an echo model, and the noise spectrum is derived statistically from measurements on actual power lines. Some measurement results on power line impedance, noise, and attenuation are presented. The results are based on measurements between line and neutral conductors in a 230 V power line network. From the results obtained so far, the impedance, noise, and attenuation of power lines exhibit variations with frequency, time, and location.

An active noise control system using online secondary path modeling with reduced auxiliary noise

Abstract: In an active noise control (ANC) system using the filtered-x least mean square (FxLMS) algorithm, an online secondary path modeling method that uses an injected auxiliary noise is often applied Such a method allows quick and full-band signal-independent modeling In addition, it is suitable for multisecondary path modeling Normally, the larger the auxiliary noise, the faster an accurate model can be obtained However, it increases the residual noise of the ANC system To mitigate this problem, in this letter, a new online secondary path modeling method is proposed Rather than fixed, the power of auxiliary noise is varied according to the working status of the ANC system More specifically, the auxiliary noise is large before the ANC system converges, and becomes small when the system converges Computer simulations show its effectiveness and robustness

Channel estimation and compensation techniques for use in frequency division multiplexed systems

Abstract: Methods and apparatus for performing channel estimate updates in frequency division multiplexed, e.g., (OFDM), systems are described. After generation of initial channel estimates from received pilots, channel estimates corresponding to individual tones are updated using any one of a plurality of update techniques including, e.g., a constant modulus based method and a reduced constellation decision directed update method. The channel estimate update technique to be used with for an individual tone is selected based on a comparison of a signal noise measurement to one or more thresholds. The channel estimate update technique applied to different tones of the OFDM signal at the same time may vary. Over time, as the level of noise is reduced, the channel estimate update technique will switch from an interpolated pilot method, to a constant modulus algorithm based method, to a reduced constellation decision directed method, to a full constellation decision directed update method.

Non-linear transformations of the feature space for robust Speech Recognition

Abstract: The noise usually produces a non-linear distortion of the feature space considered for Automatic Speech Recognition. This distortion causes a mismatch between the training and recognition conditions which significantly degrades the performance of speech recognizers. In this contribution we analyze the effect of the additive noise over cepstral based representations and we compare several approaches to compensate this effect. We discuss the importance of the non-linearities introduced by the noise and we propose a method (based on the histogram equalization technique) specifically oriented to the compensation of the non-linear transformation caused by the additive noise. The proposed method has been evaluated using the AURORA-2 database and task. The recognition results show significant improvements with respect to other compensation methods reported in the bibliography and reveals the importance of the non-linear effects of the noise and the utility of the proposed method.

Magnetoencephalography: the art of finding a needle in a haystack

Abstract: The brain's magnetic signals are much weaker than the magnetic disturbances inside the typical commercial magnetically-shielded room. Magnetic noise arises from far-field environmental sources (power lines, vehicles, etc.) and from near-field biological sources (electrically active tissues, such as muscle, heart, unwanted brain signals, etc.). Some form of inverse solution is generally used to solve for the sources that account for the MEG measurements. However, the inversion problem is non-unique and ill defined. Given the large amounts of noise and the non-uniqueness, how can MEG inversion succeed? One must provide methods for efficient attenuation of environmental noise, combined with MEG localization methods that are robust against the background clutter. Noise cancellation methods will be reviewed, and it will be shown that a combination of synthetic gradiometers, adaptive signal processing, and moderately shielded rooms can provide environmental noise attenuation in excess of 10 7 . Two types of MEG signal analysis techniques will be discussed: those depending solely on prior noise cancellation (e.g., equivalent current dipole fit and minimum norm), and those intrinsically providing additional cancellation of far and near field noise (e.g., beamformers). The principles and behavior of beamformers for variations in signal and noise will be explained. Several beamformer classes will be discussed, and the presentation will conclude with examples of their clinical applications.

A 5.8 GHz fully integrated low power low phase noise CMOS LC VCO for WLAN applications

Abstract: A fully integrated low power and low phase noise 5.8 GHz VCO is designed and fabricated in standard 0.24 /spl mu/m single-poly, 5-metal digital CMOS process. The VCO-core draws 2 mA of current from a 2.5 V supply. Measured phase noise at 1 MHz offset from the center frequency is -112 dBc/Hz. It has a tuning range of 810 MHz with low phase noise performance throughout the tuning range. It meets the requirements for IEEE802.11a WLAN standard. Low power and low phase noise have been achieved simultaneously by the use of np complementary cross-coupled topology. The novel orientation of the inductor pair used in the design minimizes the effect of any unwanted common-mode magnetic coupling that may arise from other on-chip inductors in an integrated environment.

Efficient approximation of neural filters for removing quantum noise from images

Abstract: In this paper, efficient filters are presented that approximate neural filters (NFs) that are trained to remove quantum noise from images. A novel analysis method is proposed for making clear the characteristics of the trained NF. In the proposed analysis method, an unknown nonlinear deterministic system with plural inputs such as the trained NF can be analyzed by using its outputs when the specific input signals are input to it. The experiments on the NFs trained to remove quantum noise from medical and natural images were performed. The results have demonstrated that the approximate filters, which are realized by using the results of the analysis, are sufficient for approximation of the trained NFs and efficient at computational cost.

Microphone array post-filtering for non-stationary noise suppression

Abstract: Microphone array post-filtering allows additional reduction of noise components at a beamformer output. Existing techniques are either restricted to classical delay-and-sum beamformers, or are based on single-channel speech enhancement algorithms that are inefficient at attenuating highly non-stationary noise components. In this paper, we introduce a microphone array post-filtering approach, applicable to adaptive beamformer, that differentiates non-stationary noise components from speech components. The ratio between the transient power at the beamformer primary output and the transient power at the reference noise signals is used for indicating whether such a transient is desired or interfering. Based on a Gaussian statistical model and combined with an appropriate spectral enhancement technique, a significantly reduced level of non-stationary noise is achieved without further distorting speech components. Experimental results demonstrate the effectiveness of the proposed method.