A glimpsing model of speech perception in noise

Do listeners process noisy speech by taking advantage of "glimpses"-spectrotemporal regions in which the target signal is least affected by the background? This study used an automatic speech recognition system, adapted for use with partially specified inputs, to identify consonants in noise. Twelve masking conditions were chosen to create a range of glimpse sizes. Several different glimpsing models were employed, differing in the local signal-to-noise ratio (SNR) used for detection, the minimum glimpse size, and the use of information in the masked regions. Recognition results were compared with behavioral data. A quantitative analysis demonstrated that the proportion of the time-frequency plane glimpsed is a good predictor of intelligibility. Recognition scores in each noise condition confirmed that sufficient information exists in glimpses to support consonant identification. Close fits to listeners' performance were obtained at two local SNR thresholds: one at around 8 dB and another in the range -5 to -2 dB. A transmitted information analysis revealed that cues to voicing are degraded more in the model than in human auditory processing.     

Two-parametric model of the spectrum of traffic noise in Tomsk

The technique of mapping urban noise is proposed on the basis of a two-parameter model of the acoustic noise spectrum. The acoustic noise and spatial distribution of the decay rate in Tomsk are mapped. The factors influencing the formation of the acoustic noise of traffic flow are described. Analysis is performed on how different operating modes of a vehicle??s internal combustion engine affect the background level of acoustic noise.     

A hybrid detrending method for fractional Gaussian noise

Determining trend and implementing detrending operations are important steps in data analysis. Yet there is neither precise definition of “trend” nor any logical algorithm for extracting it. In this paper, we propose a Hybrid Detrending Method (HDM) which is based on the Empirical Mode Decomposition (EMD) and the Detrended Fluctuation Analysis (DFA). Our method can remove the polynomial and sinusoidal trends from the fractional Gaussian noise (fGn) background. We illustrate the method by selected examples from artificial time series and climate data. In comparison with existing frequency domain based detrending methods, our method is a posteriori, the trend defined by our method is only derived from the data. Further, our method also preserves the scaling behavior of the original signals.     

Fluctuation spectrum in an exactly solvable model with dissipation: A new model of the Flicker noise

A system is considered consisting of a harmonic oscillator and a field interacting with it. A quadratic Lagrangian is used, so that the model is exactly solvable. Under some conditions, the model exhibits a dissipative behavior of a selected oscillator. A canonical transformation is found which brings the Hamiltonian to a diagonal form, which is used to compute the quantum correlation and spectral functions of the oscillator fluctuations. It is found that the model allows for a low-frequency spectrum of the form for the driving force, and for the oscillator coordinate (Flicker noise).Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 10, pp. 13–18, October, 1990.     

Frequency discrimination of tones presented in filtered noise

Previous research (Emmerich et al., 1983) in which tones were presented in the center of the notches in band-reject noise backgrounds suggests that information from frequency regions remote from the nominal signal frequency is useful in frequency discrimination. The present work extends the earlier findings by presenting tones on either side of a notch so that only one (or the other) tail of the excitation patterns of the tones would fall into the notch. In addition, tones were presented in high-pass noise, low-pass noise, and various combinations of the two. The results again indicate that remote information affects frequency discrimination, and they are also consistent with the hypothesis that the low-frequency tail of the excitation pattern is more useful for frequency discrimination than is the high-frequency tail.     

Lagrangian boundary condition and non-linear propagation as causes of Gaussian noise spectrum deformation

In this paper a novel analytical method of spectral analysis for acoustic Gaussian noise signals propagated in lossless fluids is presented. The starting point for theoretical considerations is the “input” signal transformation given by Earnshaw's parametric solution. By using a method of parameter elimination, based upon the filtering property of the delta function and its spectral representation, and utilizing a new theorem concerning continuous stochastic processes, an integral formula which allows one to map the power spectrum of the input signal (i.e., the boundary condition of Lagrange or the boundary condition of Euler) into the power spectrum of the particle velocity for an arbitrary point of the acoustic field (before the shock formation), is derived. The final formulae are well-adapted to numerical calculations of “output” spectra by electronic means.     

Evaluation of a spectrum target prediction model in speech perception

A model of a spectrum target prediction mechanism is proposed and evaluated by comparing predicted values with results of psychoacoustic experiments. When the trajectory of the cepstrally smoothed LPC spectrum is approximated by a second-order critically damped system, the proposed model can estimate target values using short-period spectrum sequences (50 ms) without being given the onset positions of the spectral transition. Additionally, this model decreases the length of transitional sounds and recovers vowel characteristics neutralized by coarticulation. Moreover, this model compensates for the transitions of syllables and extracts stable characteristics from syllable transitions. This model is applicable to coarticulation recovery in speech signal processing.     

Multiplicative non-Gaussian noise and additive Gaussian white noise induced transition in a piecewise nonlinear model

We study the transition problems in a piecewise nonlinear model induced by correlated multiplicative non-Gaussian noise and additive Gaussian white noise. Firstly, applying the path integral approach, the unified colored noise approximation, the analytical expression of the steady-state probability density function (SPD) is derived. Then the change regulation of the SPD is analyzed with the change of the strength and relevance of multiplicative noise and additive noise. From numerical computations we obtain some new nonlinear phenomena: the transition can be induced by the cross-correlation strength between noises, the non-Gaussian noise intensity and the Gaussian noise intensity as well as the non-Gaussian noise deviation parameter. This indicates that the effect of the non-Gaussian noise intensity on SPD is the same as that of the Gaussian noise intensity. Moreover, we also find the correlation time of the non-Gaussian noise can not induce the transition.     

Langevin particle in Gaussian noise

The problem of memory of past is discussed for a Langevin particle subject to Gaussian noise of a general type. The most probable trajectories of a particle are found and a generalisation of the Girsanov formula is proposed.     

A spread spectrum technique for the study of outdoor noise propagation

This paper describes field measurements to assess innovative correlation techniques for the study of meteorological and topographical effects on sound propagation. To take advantage of the properties of coded signals in a time-varying system, the correlation signal is produced by the modulation of a code sequence onto an acoustic carrier. An established method of increasing signal-to-noise ratio is to use correlation techniques with maximum length sequences. However, this standard method is restricted in its use outdoors because of the time-variant nature of the atmosphere. On the other hand, the correlation properties of a directly carrier-modulated code sequence modulation signal may be exploited in a time-varying environment. An experiment is described in which the correlation properties of the spread spectrum signal are demonstrated and are used to calculate accurate times of flight that compare well with sonic anemometer measurements of speed of sound. The results illustrate that an acoustical spread spectrum system can provide significantly improved ways of measuring sound propagation outdoors.     

Modulation and gap detection for broadband and filtered noise signals

Modulation detection thresholds (as a function of sinusoidal amplitude modulation frequency) and temporal gap detection thresholds were measured for three low-pass-filtered noise signals (fc = 1000, 2000, and 4000 Hz), a high-pass-filtered noise signal (fc = 4000 Hz), and a broadband signal. The two latter noise signals were effectively low-pass filtered (fc = 6500 Hz) by the earphone. Each of the filtered signals was presented with a complementary filtered noise masker. Modulation and gap detection thresholds were lowest for the broadband and high-pass signals. Thresholds were significantly higher for the low-pass signals than for the broadband and high-pass signals. For these tasks and conditions, the high-frequency content of the noise signal was more important than was the signal bandwidth. Sensitivity (s) and time constant (tau) indices were derived from functions fitted to the modulation detection data. These indices were compared with gap detection thresholds for corresponding signals. The gap detection thresholds were correlated inversely (rho = -1.0, p less than 0.05) with s (i.e., smaller gap detection thresholds were correlated with greater sensitivity to modulation), but were not correlated significantly with tau, which was relatively invariant across signal conditions.     

Theory of nonlinear Gaussian noise

We consider stochastic differential equations of the Langevin type in which the noise enters nonlinearly. In particular we study quadratic gaussian noise and we derive equations for the probability density under different approximations. In the limit of small intensity and small correlation time of the noise we obtain a Fokker-Planck equation which accounts for the main effects of the nonlinear noise. We present some examples and we discuss the consequences of our results in the analysis of an electrohydrodynamic instability in liquid crystals in the presence of external noise.     

A central spectrum model: a synthesis of auditory-nerve timing and place cues in monaural communication of frequency spectrum

A probabilistic psychophysical model for monaural communication from the auditory nerve to the brain is given in the form of a tonotopic display of stimulus spectrum, termed central spectrum. The model builds upon prior research demonstrating the potential of neural timing cues from the auditory nerve for conveying information on complex spectra, and was designed to meet the quantified demands of the psychophysics of frequency measurement. The central spectrum magnitude at each frequency is determined by the response of the auditory-nerve fibre with characteristic frequency matching that frequency. An interval histogram from each fiber is passed through a filter matched to the characteristic frequency of the fiber. This output versus characteristic frequency defines the central spectrum. Detailed analysis demonstrates that efficient probabilistic processing of the central spectrum described known psychophysical properties of frequency measurement in discrimination and periodicity pitch experiments. Psychophysical models based upon the central spectrum model followed by optimum probabilistic pattern recognition are potentially relevant for predicting human communication limits in response to arbitrary sounds of speech and music.     

A computer model for the prediction of factory noise

A computer program which calculates noise levels around a factory floor has been written. The collection of data for input to the program, formulae used in the calculation of noise levels and output from the program are described.The program has been tested using data collected in a variety of workshops and factories. The results of two of these case studies are discussed, together with overall results for all cases considered, which show that the program can predict sound levels with a high degree of accuracy.An interactive version of the program which enables a user to see immediately how certain changes to the data will affect noise levels is also described.     

舰船噪声小波谱提取方法研究

人耳听测舰船噪声的特征,是声纳员非常重要的专业技能。本文根据小波变换与人耳蜗频率响应相近似的特点,以cmor1-0.5母小波为基础,构造了一系列基于小波变换的滤波器组。对于小波谱提取中涉及的带宽、分辨率等参数进行了分析,提出了小波谱提取过程中改善分辨率的办法。为检验该方法的可行性,对三种不同类型的舰船噪声进行了小波谱分析,与其FFT谱图进行了比较。为解决小波谱提取过程中高分辨率与计算量的矛盾,提出了对指定频带进行小波谱分析的方法,解决了计算量的问题。     

高斯噪声中的参数盲估计

一般的盲信号处理方法常忽略噪声的影响,而实际问题中噪声的影响是存在的。本文主要讨论了在协方差矩阵未知的加性高斯噪声中混合系数的盲估计问题。以最大似然估计为基础,本文提出一种求解参数的最优化算法,并给出了混合矩阵和协方差矩阵的计算式。采用高斯混合模型(GMM)来逼近源信号的概率密度函数,简化了算法中的积分,导出了一种实用的期望最大算法(EM)算法迭代式。计算机仿真结果表明,算法不仅能稳定收敛,而且在低信噪比下的性能也很好。     

A measurement model for general noise reaction in response to aircraft noise

In this paper a measurement model for general noise reaction (GNR) in response to aircraft noise is developed to assess the performance of aircraft noise annoyance and a direct measure of general reaction as indicators of this concept. For this purpose GNR is conceptualized as a superordinate latent construct underlying particular manifestations. This conceptualization is empirically tested through estimation of a second-order factor model. Data from a community survey at Frankfurt Airport are used for this purpose (N=2206). The data fit the hypothesized factor structure well and support the conceptualization of GNR as a superordinate construct. It is concluded that noise annoyance and a direct measure of general reaction to noise capture a large part of the negative feelings and emotions in response to aircraft noise but are unable to capture all relevant variance. The paper concludes with recommendations for the valid measurement of community reaction and several directions for further research.