Spectro-temporal integration in signal detection

This paper is concerned with aspects of temporal integration and across-frequency integration in signal detection. Previous experiments on the detection of brief broadband signals (clicks) in continuous broadband noise revealed efficient spectral integration. The extent to which this effect is restricted to a critical time window was investigated by manipulating the temporal relations among the signal components in different frequency regions. In a typical experiment, the signal consists of nine brief Gaussian-shaped tone pulses, equally distributed at 1/3-oct intervals, each with a spectral width of about 1/3 oct, and each equally detectable in white noise. In the synchronized condition (i.e. coinciding peaks of the nine Gaussian envelopes), the detection threshold is reached when the levels of the nine individual tone pulses are about 8 dB below their individual threshold levels (efficient spectral integration). When the signal is progressively desynchronized (i.e. noncoinciding peaks of the Gaussian envelopes), detection threshold is found to increase. This suggests that efficient spectral integration in signal detection is confined to a narrow time window, with a typical value of 30 ms. Similar experiments were performed with respect to the efficiency of temporal integration. For constant-duration signals (100 ms), the detection threshold is found to increase when progressively widening signal bandwidth. The data indicate that the efficient temporal integration in signal detection is confined to a narrow frequency window, which, not surprisingly, corresponds to the critical bandwidth.     

Spectro-temporal analysis in normal-hearing and cochlear-impaired listeners

Detection thresholds for a 1.0-kHz pure tone were determined in unmodulated noise and in noise modulated by a 15-Hz square wave. Comodulation masking release (CMR) was calculated as the difference in threshold between the modulated and unmodulated conditions. The noise bandwidth varied between 100 and 1000 Hz. Frequency selectivity was also examined using an abbreviated notched-noise masking method. The subjects in the main experiment consisted of 12 normal-hearing and 12 hearing-impaired subjects with hearing loss of cochlear origin. The most discriminating conditions were repeated on 16 additional hearing-impaired subjects. The CMR of the hearing-impaired group was reduced for the 1000-Hz noise bandwidth. The reduced CMR at this bandwidth correlated significantly with reduced frequency selectivity, consistent with the hypothesis that the across-frequency difference cue used in CMR is diminished by poor frequency selectivity. The results indicated that good frequency selectivity is a prerequisite, but not a guarantee, of large CMR.     

Real-time fractal signal processing in the time domain

Fractal analysis has proven useful for the quantitative characterization of complex time series by scale-free statistical measures in various applications. The analysis has commonly been done offline with the signal being resident in memory in full length, and the processing carried out in several distinct passes. However, in many relevant applications, such as monitoring or forecasting, algorithms are needed to capture changes in the fractal measure real-time. Here we introduce real-time variants of the Detrended Fluctuation Analysis (DFA) and the closely related Signal Summation Conversion (SSC) methods, which are suitable to estimate the fractal exponent in one pass. Compared to offline algorithms, the precision is the same, the memory requirement is significantly lower, and the execution time depends on the same factors but with different rates. Our tests show that dynamic changes in the fractal parameter can be efficiently detected. We demonstrate the applicability of our real-time methods on signals of cerebral hemodynamics acquired during open-heart surgery.     

Spectro-temporal modulation transfer functions and speech intelligibility

Detection thresholds for spectral and temporal modulations are measured using broadband spectra with sinusoidally rippled profiles that drift up or down the log-frequency axis at constant velocities. Spectro-temporal modulation transfer functions (MTFs) are derived as a function of ripple peak density (omega cycles/octave) and drifting velocity (omega Hz). The MTFs exhibit a low-pass function with respect to both dimensions, with 50% bandwidths of about 16 Hz and 2 cycles/octave. The data replicate (as special cases) previously measured purely temporal MTFs (omega = 0) [Viemeister, J. Acoust. Soc. Am. 66, 1364-1380 (1979)] and purely spectral MTFs (omega = 0) [Green, in Auditory Frequency Selectivity (Plenum, Cambridge, 1986), pp. 351-359]. A computational auditory model is presented that exhibits spectro-temporal MTFs consistent with the salient trends in the data. The model is used to demonstrate the potential relevance of these MTFs to the assessment of speech intelligibility in noise and reverberant conditions.     

Real-time processing using the frequency domain binaural model

There are many approaches to achieving high-performance speech enhancement. The modeling of the human auditory system is a good approach, since human beings can focus on target speech under concurrent speech conditions. One example of the binaural models is the time domain binaural model. However, this model has a high-calculation cost because the algorithm is based on auto-correlation, which is computationally intensive. Another example is the frequency domain binaural model proposed by Nakashima et al. [Nakashima H, Chisaki Y, Usagawa T, Ebata M. Frequency domain binaural model based on interaural phase and level differences. Acoust Sci Technol 2003;24(4):172-8]. Since the frequency domain binaural model uses the fast fourier transform, the calculation cost is much lower than that of the time domain binaural model. Therefore, it is not difficult to perform real-time processing using recent hardware such as digital signal processors and even laptop personal computers. However the quality of the segregated sound obtained using the frequency domain binaural model depends on system parameters such as frequency resolution and frame shift length for overlap adding in time domain. This paper introduces the construction of a prototype of a hearing assistant system based on the frequency domain binaural model. The detailed implementation techniques and parameter tuning are mentioned. The proposed system runs in real-time after parameter tuning. The directional attenuation levels, that is, the directivity patterns of the proposed system is measured. Finally, it is shown that the prototype can extract sounds coming from specific directions in real-time.     

Spectro-temporal modulation energy based mask for robust speaker identification

Spectro-temporal modulations of speech encode speech structures and speaker characteristics. An algorithm which distinguishes speech from non-speech based on spectro-temporal modulation energies is proposed and evaluated in robust text-independent closed-set speaker identification simulations using the TIMIT and GRID corpora. Simulation results show the proposed method produces much higher speaker identification rates in all signal-to-noise ratio (SNR) conditions than the baseline system using mel-frequency cepstral coefficients. In addition, the proposed method also outperforms the system, which uses auditory-based nonnegative tensor cepstral coefficients [Q. Wu and L. Zhang, "Auditory sparse representation for robust speaker recognition based on tensor structure," EURASIP J. Audio, Speech, Music Process. 2008, 578612 (2008)], in low SNR (≤ 10 dB) conditions.     

Spectro-temporal envelope changes caused by temporal fine structure modification

The study of speech from which the temporal fine structure (TFS) has been removed has become an important research area. Common procedures for removing TFS include noise and tone vocoders. In the noise vocoder, bands of noise are modulated by the envelope of the speech within each band, and in the tone vocoder the carrier is a sinusoid at the center of each frequency band. Five different procedures for removing TFS are evaluated in this paper: the noise vocoder, a low-noise noise approach in which the noise envelope is replaced by the speech envelope in each frequency band, phase randomization within each band, the tone vocoder, and sinusoidal modeling with random phase. The effects of TFS modification on the speech envelope are evaluated using an index based on the envelope time-frequency modulation. The results show that for all of the TFS techniques implemented in this study, there is a substantial loss in the accuracy of reproduction of the envelope time-frequency modulation. The tone vocoder gives the best accuracy, followed by the procedure that replaces the noise envelope with the speech envelope in each band.     

Spectro-temporal modulation subspace-spanning filter bank features for robust automatic speech recognition

In an attempt to increase the robustness of automatic speech recognition (ASR) systems, a feature extraction scheme is proposed that takes spectro-temporal modulation frequencies (MF) into account. This physiologically inspired approach uses a two-dimensional filter bank based on Gabor filters, which limits the redundant information between feature components, and also results in physically interpretable features. Robustness against extrinsic variation (different types of additive noise) and intrinsic variability (arising from changes in speaking rate, effort, and style) is quantified in a series of recognition experiments. The results are compared to reference ASR systems using Mel-frequency cepstral coefficients (MFCCs), MFCCs with cepstral mean subtraction (CMS) and RASTA-PLP features, respectively. Gabor features are shown to be more robust against extrinsic variation than the baseline systems without CMS, with relative improvements of 28% and 16% for two training conditions (using only clean training samples or a mixture of noisy and clean utterances, respectively). When used in a state-of-the-art system, improvements of 14% are observed when spectro-temporal features are concatenated with MFCCs, indicating the complementarity of those feature types. An analysis of the importance of specific MF shows that temporal MF up to 25 Hz and spectral MF up to 0.25 cycles/channel are beneficial for ASR.     

Comparison of level discrimination, increment detection, and comodulation masking release in the audio- and envelope-frequency domains

In general, the temporal structure of stimuli must be considered to account for certain observations made in detection and masking experiments in the audio-frequency domain. Two such phenomena are (1) a heightened sensitivity to amplitude increments with a temporal fringe compared to gated level discrimination performance and (2) lower tone-in-noise detection thresholds using a modulated masker compared to those using an unmodulated masker. In the current study, translations of these two experiments were carried out to test the hypothesis that analogous cues might be used in the envelope-frequency domain. Pure-tone carrier amplitude-modulation (AM) depth-discrimination thresholds were found to be similar using both traditional gated stimuli and using a temporally modulated fringe for a fixed standard depth (ms = 0.25) and a range of AM frequencies (4-64 Hz). In a second experiment, masked sinusoidal AM detection thresholds were compared in conditions with and without slow and regular fluctuations imposed on the instantaneous masker AM depth. Release from masking was obtained only for very slow masker fluctuations (less than 2 Hz). A physiologically motivated model that effectively acts as a first-order envelope change detector accounted for several, but not all, of the key aspects of the data.     

超宽带散射信号的时域测量及处理

叙述了在超宽带电磁脉冲照射下良导电散射体散射信号的时域测量技术及数据处理方法。描述了产生散射信号的物理过程,散射信号的时域测量步骤、提取方法以及散射体冲激响应的计算方法。通过对铝金属球体散射信号的测量及处理,说明了上述测量技术和数据处理方法是有效的,基本满足逆散射成像的要求。     

轴向B-dot束流偏角探测器信号的频域处理北大核心CSCD

提出一种针对轴向B-dot束流偏角探测器信号的频域处理方法,从探测器本身的频域响应出发,并从探测器信号的频谱中提取有效信息,能够一定程度上消除束流横向偏移对偏角测量的干扰。该方法是对时域分析法处理轴向B-dot信号的一种补充,相比于时域法的一阶近似,对信号频谱的处理更接近对复杂真实情况的近似,但并未从根本上解决由安装误差等原因导致束流横向偏移而带来的测量不准确。从标定试验台测试结果来看,该方法的测试精度与时域法相当,约1mrad。     

轴向B-dot束流偏角探测器信号的频域处理

提出一种针对轴向B-dot束流偏角探测器信号的频域处理方法,从探测器本身的频域响应出发,并从探测器信号的频谱中提取有效信息,能够一定程度上消除束流横向偏移对偏角测量的干扰。该方法是对时域分析法处理轴向B-dot信号的一种补充,相比于时域法的一阶近似,对信号频谱的处理更接近对复杂真实情况的近似,但并未从根本上解决由安装误差等原因导致束流横向偏移而带来的测量不准确。从标定试验台测试结果来看,该方法的测试精度与时域法相当,约1 mrad。     

非消声水池中低频换能器测量的空间域处理方法

提出了一种在非消声水池中低频换能器测量的空间域处理方法。该方法是在发射和接收换能器保持相对位置不变的情况下,通过多次无规则变换其在有限水域中的位置,让同频反射声的干扰贡献随机和无规则化,最终将上述所有位置接收的信号同步叠加而将同频反射声干扰消除,从而提取出了所需的直达波波形信号,克服了传统的脉冲测量技术受同频反射声干扰无法提取直达信号的问题。在5 m×7 m×6 m非消声水池,测量换能器样品,测量频率范围是400~2500 Hz,测量得到的结果与湖上测试结果相比,两者基本一致。该方法的实现,大大的提高了非消声水池的低频换能器测试能力,有效测量频率下限比一般脉冲测试方法降低一个数量级。     

Multiple-image hiding in the Fresnel domain

To avoid additive cross-talk among multiple images, they are separated from each other and even from the host image in the hiding and the extraction process by locating them independently in the Fresnel domain with computer-generated double phase-only masks. Gray images and white-ground and black-ground binary images can be hidden in the system at the same time. The hiding capacity of the system as to these three types of multiple image has also been investigated using a cascaded iterative algorithm. The security and the multiplexing parameters of the system are analyzed as well.     

Stationary structure of the domain wall of the soft magnetic bubble domain

A simple method for calculating the barrel-like curvature of a bubble domain is developed. The results obtained are compared with the results of the Thiele theory.