Different Levels Of Background Noise Research Articles

Equivalent Source Method-Based Nearfield Acoustic Holography in a Moving Medium

To identify sound sources situated in a fluid flow, an equivalent source method (ESM)-based nearfield acoustic holography (NAH) in a moving medium is proposed, and two types of acoustic inputs, pressure and particle velocity, are considered. In particular, an analytical relationship between the particle velocity perpendicular to the flow direction and the equivalent source strength is deduced, which makes it possible to realize the reconstruction with particle velocity input. Compared to the planar NAH in a moving medium, the proposed method is applicable to sound sources with more complicated geometries. Numerical simulations with sound sources distributed over two types of geometries including planar geometry and nonplanar one are conducted to test the performances of the proposed method. The results indicate that the proposed method provides satisfactory reconstructed results whatever with pressure input or with particle velocity input, and it is valid and robust over a wide range of flow velocities and frequencies and under different levels of background noise.

Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy

Abstract. We present a workflow for efficient construction and calibration of large-scale groundwater models that includes the integration of airborne electromagnetic (AEM) data and hydrological data. In the first step, the AEM data are inverted to form a 3-D geophysical model. In the second step, the 3-D geophysical model is translated, using a spatially dependent petrophysical relationship, to form a 3-D hydraulic conductivity distribution. The geophysical models and the hydrological data are used to estimate spatially distributed petrophysical shape factors. The shape factors primarily work as translators between resistivity and hydraulic conductivity, but they can also compensate for structural defects in the geophysical model. The method is demonstrated for a synthetic case study with sharp transitions among various types of deposits. Besides demonstrating the methodology, we demonstrate the importance of using geophysical regularization constraints that conform well to the depositional environment. This is done by inverting the AEM data using either smoothness (smooth) constraints or minimum gradient support (sharp) constraints, where the use of sharp constraints conforms best to the environment. The dependency on AEM data quality is also tested by inverting the geophysical model using data corrupted with four different levels of background noise. Subsequently, the geophysical models are used to construct competing groundwater models for which the shape factors are calibrated. The performance of each groundwater model is tested with respect to four types of prediction that are beyond the calibration base: a pumping well's recharge area and groundwater age, respectively, are predicted by applying the same stress as for the hydrologic model calibration; and head and stream discharge are predicted for a different stress situation. As expected, in this case the predictive capability of a groundwater model is better when it is based on a sharp geophysical model instead of a smoothness constraint. This is true for predictions of recharge area, head change, and stream discharge, while we find no improvement for prediction of groundwater age. Furthermore, we show that the model prediction accuracy improves with AEM data quality for predictions of recharge area, head change, and stream discharge, while there appears to be no accuracy improvement for the prediction of groundwater age.

Online testing for assessing speech intelligibility

The use of online testing in the behavioral sciences is increasing due to the potential for lower cost and faster completion than traditional in-person laboratory testing. Online testing presents a special challenge for speech research due to the variety of listeners’ acoustic environments. For example, listeners may use headphones or speakers of various types, complete the task in different levels of background noise, or vary in their hearing abilities. Here we presented spoken sentences in speech-shaped noise to participants from the United States recruited online using Amazon Mechanical Turk at SNRs of -2, -5, and -8 dB (n≥50 per SNR). We compared these online results to normative data collected using these same sentences in the lab (SNR of -5 dB; n = 30). Preliminary results suggest a reasonable correspondence between average intelligibility scores for individual sentences presented using the two methods (Spearman rho = 0.79). Standard deviations suggest greater variability in the online responses (average SD across sentences = 1.24) relative to the lab responses (average SD = 0.86). We conclude that despite increased variability, online testing can provide reasonable ratings of intelligibility and in many circumstances is a feasible method to supplement or replace laboratory testing.

MBDDiff: an R package designed specifically for processing MBDcap-seq datasets.

BackgroundSince its initial discovery in 1975, DNA methylation has been intensively studied and shown to be involved in various biological processes, such as development, aging and tumor progression. Many experimental techniques have been developed to measure the level of DNA methylation. Methyl-CpG binding domain-based capture followed by high-throughput sequencing (MBDCap-seq) is a widely used method for characterizing DNA methylation patterns in a genome-wide manner. However, current methods for processing MBDCap-seq datasets does not take into account of the region-specific genomic characteristics that might have an impact on the measurements of the amount of methylated DNA (signal) and background fluctuation (noise). Thus, specific software needs to be developed for MBDCap-seq experiments.ResultsA new differential methylation quantification algorithm for MBDCap-seq, MBDDiff, was implemented. To evaluate the performance of the MBDDiff algorithm, a set of simulated signal based on negative binomial and Poisson distribution with parameters estimated from real MBDCap-seq datasets accompanied with different background noises were generated, and then performed against a set of commonly used algorithms for MBDCap-seq data analysis in terms of area under the ROC curve (AUC), number of false discoveries and statistical power. In addition, we also demonstrated the effective of MBDDiff algorithm to a set of in-house prostate cancer samples, endometrial cancer samples published earlier, and a set of public-domain triple negative breast cancer samples to identify potential factors that contribute to cancer development and recurrence.ConclusionsIn this paper we developed an algorithm, MBDDiff, designed specifically for datasets derived from MBDCap-seq. MBDDiff contains three modules: quality assessment of datasets and quantification of DNA methylation; determination of differential methylation of promoter regions; and visualization functionalities. Simulation results suggest that MBDDiff performs better compared to MEDIPS and DESeq in terms of AUC and the number of false discoveries at different levels of background noise. MBDDiff outperforms MEDIPS with increased backgrounds noise, but comparable performance when noise level is lower. By applying MBDDiff to several MBDCap-seq datasets, we were able to identify potential targets that contribute to the corresponding biological processes. Taken together, MBDDiff provides user an accurate differential methylation analysis for data generated by MBDCap-seq, especially under noisy conditions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2794-z) contains supplementary material, which is available to authorized users.

Lip Contact Pressure While Talking in Background Noise

Loudness manipulation is an important clinical tool in reducing functional communication limitations and increasing speaking participation in individuals with dysarthria. Increasing loudness appears to influence all domains of the speech production system (i.e., respiratory, laryngeal, and orofacial), resulting in increased effort and coordination. The purpose of the present study was to investigate the influence speaking under different levels of background noise has on lip contact pressure, a measure of physiological effort, during bilabial consonant production. Ten young adults ranging in age from 20 to 24 years read 30 sentences under three different levels of multitalker babble background noise (0, 40, & 80 dBHL). An Entran Pressure Transducer was used to acquire lip contact pressure for words containing the bilabial consonants /p/, /b/, and /m/. Intensity of the voice significantly increased across noise conditions; however, static and dynamic measures of articulatory contact pressures (ACP) were not significantly influenced by background noise. Increase in physiological effort as represented by ACP appears not be related to increasing intensity while speaking in background noise. Additional study of the factors influencing different aspects of articulatory contact pressure is recommended for individuals with and without motor speech disorders.

SNR-Invariant PLDA Modeling in Nonparametric Subspace for Robust Speaker Verification

While i-vector/PLDA framework has achieved great success, its performance still degrades dramatically under noisy conditions. To compensate for the variability of i-vectors caused by different levels of background noise, this paper proposes an SNR-invariant PLDA framework for robust speaker verification. First, nonparametric feature analysis (NFA) is employed to suppress intra-speaker variation and emphasize the discriminative information inherited in the boundaries between speakers in the i-vector space. Then, in the NFA-projected subspace, SNR-invariant PLDA is applied to separate the SNR-specific information from speaker-specific information using an identity factor and an SNR factor. Accordingly, a projected i-vector in the NFA subspace can be represented as a linear combination of three components: speaker, SNR, and channel. During verification, the variability due to SNR and channels are integrated out when computing the marginal likelihood ratio. Experiments based on NIST 2012 SRE show that the proposed framework achieves superior performance when compared with the conventional PLDA and SNR-dependent mixture of PLDA.

Hearing loss impacts neural alpha oscillations under adverse listening conditions.

Degradations in external, acoustic stimulation have long been suspected to increase the load on working memory (WM). One neural signature of WM load is enhanced power of alpha oscillations (6–12 Hz). However, it is unknown to what extent common internal, auditory degradation, that is, hearing impairment, affects the neural mechanisms of WM when audibility has been ensured via amplification. Using an adapted auditory Sternberg paradigm, we varied the orthogonal factors memory load and background noise level, while the electroencephalogram was recorded. In each trial, participants were presented with 2, 4, or 6 spoken digits embedded in one of three different levels of background noise. After a stimulus-free delay interval, participants indicated whether a probe digit had appeared in the sequence of digits. Participants were healthy older adults (62–86 years), with normal to moderately impaired hearing. Importantly, the background noise levels were individually adjusted and participants were wearing hearing aids to equalize audibility across participants. Irrespective of hearing loss (HL), behavioral performance improved with lower memory load and also with lower levels of background noise. Interestingly, the alpha power in the stimulus-free delay interval was dependent on the interplay between task demands (memory load and noise level) and HL; while alpha power increased with HL during low and intermediate levels of memory load and background noise, it dropped for participants with the relatively most severe HL under the highest memory load and background noise level. These findings suggest that adaptive neural mechanisms for coping with adverse listening conditions break down for higher degrees of HL, even when adequate hearing aid amplification is in place.

Identification and response latencies for Mandarin-accented isolated words in quiet and in noise

This study compared the intelligibility of native and foreign-accented American English speech presented in quiet and mixed with two different levels of background noise. Two native American English speakers and two native Mandarin Chinese speakers for whom English is a second language read three 50-word lists of phonetically balanced words (Stuart, 2004). The words were mixed with noise at three different signal-to-noise levels—no noise (quiet), SNR + 10 dB (signal 10 dB louder than noise) and SNR 0 (signal and noise at equal loudness). These stimuli were presented to ten native American English listeners who were simply asked to repeat the words they heard the speakers say. Listener response latencies were measured. The results showed that for both native and accented speech, response latencies increased as the noise level increased. For words identified correctly, response times to accented speech were longer than for native speech but the noise conditions affected both types equally. For words judged incorrectly, however, the noise conditions increased latencies for accented speech more than for native speech. Overall, these results support the notion that processing accented speech requires more cognitive effort than processing native speech.

Evaluating microphones and microphone placement for signal processing and automatic speech recognition of teacher-student dialog

We evaluate a variety of audio recording techniques for a project on the automatic analysis of speech dialog in middle school and high school classrooms. In our scenario, the teacher wears a headset microphone or a lapel microphone. A second microphone is then used to collect speech and related sounds from students in the classroom. Various boundary microphones, omni-directional microphones, and cardioid microphones are tested as this second classroom microphone. A commercial microphone array [Microsoft Xbox Kinect] is also tested. We report on how well digital source-separation techniques work for segregating the teacher and student speech signals from one another based on these various microphones and placements. We also test the recordings using various automatic speech recognition engines for word recognition error rates under different levels of background noise. Preliminary results indicate one boundary microphone, the Crown PZM-30, to be superior for the classroom recordings. This is based on its performance at capturing near and distant student signals for ASR in noisy conditions, as measured by ASR error rates across different ASR engines.

Does the signal-to-noise ratio of an interlocutor influence a speaker's vocal intensity?

This study investigated whether the signal-to-noise ratio (SNR) of the interlocutor (speech partner) influences a speaker's vocal intensity in conversational speech. Twenty participants took part in artificial conversations with controlled levels of interlocutor speech and background noise. Three different levels of background noise were presented over headphones and the participant engaged in a “live interaction” with the experimenter. The experimenter's vocal intensity was manipulated in order to modify the SNR. The participants’ vocal intensity was measured. As observed previously, vocal intensity increased as background noise level increased. However, the SNR of the interlocutor did not have a significant effect on participants’ vocal intensity. These results suggest that increasing the signal level of the other party at the earpiece would not reduce the tendency of telephone users to talk loudly

Automatic onlinespike sorting with singular value decomposition and fuzzy C-mean clustering

BackgroundUnderstanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue.ResultsHere we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms.ConclusionsThis new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.

Prediction of acoustical parameters for open plan offices according to ISO 3382-3

In the new international standard ISO 3382-3 the measurement procedure for open plan offices is described and a number of new room acoustical parameters for the objective evaluation are defined. Among the new parameters are the privacy distance and the distraction distance, both derived from the STI (speech transmission index) as a function of distance from the sound source. The final evaluation is a balanced compromise between a number of parameters that depend on the amount of sound absorption, the application of screens between work stations and the level of background noise. With room acoustic simulation software these measurements can be simulated, thus providing a tool for the acoustical design of open plan offices. The paper presents an example office with a range of alternative acoustical solutions that include different amount of absorption, screens of different height, and different levels of background noise. Also the influence of dynamic background noise from people talking can be taken into account, leading to a shorter privacy distance. This provides a background for the discussion of the efficiency of various acoustical measures in open plan office design.

Acquiring L2 sentence comprehension: A longitudinal study of word monitoring in noise

This study investigated the development of second language online auditory processing with ab initio German learners of Dutch. We assessed the influence of different levels of background noise and different levels of semantic and syntactic target word predictability on word-monitoring latencies. There was evidence of syntactic, but not lexical-semantic, transfer from the L1 to the L2 from the onset of L2 learning. An initial stronger adverse effect of noise on syntactic compared to phonological processing disappeared after two weeks of learning Dutch suggesting a change towards more robust syntactic processing. At the same time the L2 learners started to exploit semantic constraints predicting upcoming target words. The use of semantic predictability remained less efficient compared to native speakers until the end of the observation period. The improvement and the persistent problems in semantic processing we found were independent of noise and rather seem to reflect the need for more context information to build up online semantic representations in L2 listening.

Multisensory processing and oscillatory activity: analyzing non-linear electrophysiological measures in humans and simians

Stimulus-related oscillations are known to be closely linked to integrative processing in the brain. One research domain within which there has been tremendous interest in oscillatory mechanisms is in the integration of inputs across the widely separated sensory systems. Under the standard approach of assessing multisensory interactions in electrophysiological datasets, the event-related response to a multisensory stimulus is directly compared with the sum of the responses to its unisensory constituents when presented alone. When using methods like wavelet transformation or fast Fourier transformation to derive induced oscillatory signals, however, such linear operations are not appropriate. Here we introduce a simple bootstrapping procedure wherein the linear summation of single unisensory trials forms a distribution against which multisensory trials may be statistically compared, an approach that circumvents the issue of non-linearity when combining unisensory oscillatory responses. To test this approach we applied it to datasets from intracranial recordings in non-human primates and human scalp-recorded EEG, both derived from a simple audio-visual integration paradigm. Significant multisensory interactions were revealed in oscillatory activity centered at 15 and 20 Hz (the so-called beta band). Simulations of different levels of background noise further validated the results obtained by this method. By demonstrating super- and sub-additive effects, our analyses showed that this approach is a valuable metric for studying multisensory interactions reflected in induced oscillatory responses.

Effects of Noise and Proficiency on Intelligibility of Chinese-Accented English

This study compared the intelligibility of native and foreign-accented bilingualism English speech presented in quiet and mixed with three different levels of background noise. Two native American English speakers and four native Mandarin Chinese speakers for whom English is a second language each read a list of 50 phonetically balanced sentences (Egan, 1948). The authors speech intelligibility identified two of the Mandarin-accented English speakers as high-proficiency speakers and two as lower proficiency speakers, based on their speech intelligibility in quiet (about 95% and 80%, respectively). Original record-perception ings and noise-masked versions of 48 utterances were presented to monolingual American English speakers. Listeners were asked to write down the words they heard the speakers say, and intelligibility was measured as content words correctly identified. While there was a modest difference between native and high-proficiency speech in quiet (about 7%), it was found that adding noise to the signal reduced the intelligibility of high-proficiency accented speech significantly more than it reduced the intelligibility of native speech. Differences between the two groups in the three added noise conditions ranged from about 12% to 33%. This result suggests that even high-proficiency non-native speech is less robust than native speech when it is presented to listeners under suboptimal conditions.

Methodology for quantifying the tonal prominence of frequency modulated tones

The paper is focused on research conducted to develop a metric to quantify the tonal prominence of frequency modulated tones in noise. Frequency modulated tones are commonly encountered in machinery noise because of RPM variations caused by changing loads and poor control in timing and repeatability of combustion events in engines, particularly diesel engines. When tonal components are noticeable they increase annoyance; thus it is important to quantify both their strength and the resulting contribution to annoyance. In preliminary work on tones with randomly varying frequencies, it was found that it is possible to remove the trackable portion of the frequency variation and use established tonal prominence metrics (Aures’ Tonality and Tone-to-Noise Ratio) on the modified signal to predict the perceived tonalness of the sounds (Lee, Hastings, Davies and Surprenant, Internoise 2003). The work presented is an extension of this earlier work: deterministic frequency variations are studied along with different levels of background noise. Modifications to the procedure to determine the strength of the tonal feature are described, as well as the issues that must be addressed before using this approach to analyze more complex machinery sounds. [Work sponsored by Caterpillar Inc.]

Effect of background noise on sound power estimates using the sound intensity technique

The presence of a background noise source affects the accuracy of the estimate of the source sound power level. In this paper, the results of a systematic experimental study on the accuracy of estimation of sound power levels in the presence of a background noise source are reported. A calibrated sound power source was used in these experiments. The sound power measurements were made using the two‐microphone sound intensity technique. The errors in the estimates of the sound power level of the calibrated sound source were determined for different levels of background noise. Also, a systematic study was made on the relationship between the number of points of measurement on the enclosing surface defined around the source and the accuracy of the sound power estimate. It has been demonstrated that the accuracy of sound power estimates is greatly improved by continuous hand scanning of the enclosing surface instead of by making measurements at a small or moderate number of fixed points. The local sound pressure minus intensity index and the global sound pressure minus intensity index are used as indicators of the data quality. [Work supported by IBM, Charlotte, NC.]

Anxiety as a function of environmental noise and social interaction.

In a study to investigate environmental noise and social interaction as simultaneous stressors affecting anxiety, three independent groups of college students (N = 48 men and women) participated in the simulation game Starpower while exposed to different levels of background noise. Intermittent white noise at 61 dB(A) and 75 dB(A) was used for the Noisy and Very Noisy conditions, respectively, and the ambient noise level of 51 dB(A) was used for Quiet. The State-Trait Anxiety Inventory, administered before and after playing the game, was used as a direct, subjective measure of anxiety. Relatively low levels of noise superimposed on the stress of social interaction influenced the level of anxiety experienced by the Ss. Groups subjected to noisier environments reported significantly stronger feelings of anxiety than those in quieter conditions (p less than .05). Ss' eyeblink rate, used as an indirect, physiological indicator of anxiety, was not significantly affected by the stress levels produced in this experiment.

The Intelligibility of Helium-Speech as a Function of Speech-to-Noise Ratio

First Page

Mechanisms of Frequency Response Extension

There is considerable evidence that subjects in a traditional psychophysical experiment act as narrow-band receivers tuned to the frequency of a known sine-wave stimulus. Obviously wave forms in real life are complex rather than simple, and the wave forms we hear can seldom be predicted exactly. A series of experiments was conducted attempting to arrive at a model for hearing when the sine-wave signal to be presented is not absolutely predictable, but might be one of two alternative frequencies. For each experimental run of 100 trials, one of two possible tones was randomly selected for presentation on each trial in a two-alternative forced-choice detection situation: one of the tones was always 1000 cy and the other had a frequency difference of 20, 100, 200, or 500 cy above or below, giving eight pairs of tones investigated. The intensities of the tones were equated for detectability in a standard single tone preliminary detection experiment. All eight pairs were run at two different levels of background noise using different signal intensities. Under these conditions differential predictions of observers' behavior with an uncertain signal can be made within the framework of the theory of signal detectability for a number of alternative models calculated to account for the extension of frequency sensitivity. The data are compared to predictions from a scanning model, a multiplex model, a threshold model, and a variable band model. (This research was carried out under sponsorship of the Operational Applications Laboratory, Air Force Cambridge Research Center and Evans Signal Laboratory, Signal Corps Engineering Laboratories, Fort Monmouth, New Jersey.)