High Levels Of Background Noise Research Articles

Noise as an Extrinsic Variable in the Animal Research Facility.

Animal research facilities are noisy environments. The high air change rates required in animal housing spaces tend to create higher noise levels from the heating and cooling systems. Housing rooms are typically constructed of hard wall material that is easily cleaned but simultaneously highly reverberant, meaning that the sound cannot be controlled/attenuated so the sounds that are generated bounce around the room uncontrolled. (Soft, sound-absorbing surfaces generally cannot be used in animal facilities because they collect microbes; various wall surface features and sound control panel options are available, although rarely used.) In addition, many of our husbandry tasks such as cage changing, animal health checks, cleaning, and transporting animals produce high levels of noise. Finally, much of the equipment we have increasingly employed in animal housing spaces, such as ventilated caging motors, biosafety, or procedure cabinets, can generate high levels of background noise, including ultrasound. These and many additional factors conspire to create an acoustic environment that is neither naturalistic nor conducive to a stress-free environment. The acoustic variability both within and between institutions can serve as an enormous confounder for research studies and a threat to our ability to reproduce studies over time and between research laboratories. By gaining a better appreciation for the acoustic variables, paired with transparency in reporting the levels, we might be able to gain a better understanding of their impacts and thereby gain some level of control over such acoustic variables in the animal housing space. The result of this could improve both animal welfare and study reproducibility, helping to address our 3Rs goals of Replacement, Reduction, and Refinement in the animal biomedical research enterprise.

Enhancing angular resolution in single-photon LIDAR for daytime long-range 3D imaging

Single photon LIDAR exhibits exceptional detection sensitivity and finds extensive applications in long-distance measurement and three-dimensional imaging domains. However, it is susceptible to background noise interference, leading to a trade-off between scanning imaging efficiency and angular resolution, thereby limiting its overall performance. In this paper, we propose a novel ‘compression-resampling’ high-resolution imaging method for single-photon scanning LIDAR based on the spatial correlation of the target scene. This approach significantly enhances the system's angular resolution without compromising imaging efficiency. By employing this method, we successfully conducted 3D imaging over distances exceeding 26 km even under challenging conditions with high levels of background noise during daylight hours. Within a target field of view measuring 1° × 1°, we reconstructed a high-resolution 3D point cloud image comprising 1000 × 1410 pixels. Notably, this achievement yielded an impressive angular resolution of 17.4 urad while maintaining an acceptable imaging time of approximately 20 minutes. The results unequivocally demonstrate the effectiveness of our proposed method in improving the quality of three-dimensional imaging and enhancing angular resolution while simultaneously reducing imaging time requirements, thus expanding potential application scenarios for single-photon LIDAR technology.

A Novel Correction Methodology to Improve the Performance of a Low-Cost Hyperspectral Portable Snapshot Camera.

The development of spectral sensors (SSs) capable of retrieving spectral information have opened new opportunities to improve several environmental and agricultural practices, e.g., crop breeding, plant phenotyping, land use monitoring, and crop classification. The SSs are classified as multispectral and hyperspectral (HS) based on the number of the spectral bands resolved and sampled during data acquisition. Large-scale applications of the HS remain limited due to the cost of this type of technology and the technical difficulties in hyperspectral data processing. Low-cost portable hyperspectral cameras (PHCs) have been progressively developed; however, critical aspects associated with data acquisition and processing, such as the presence of spectral discontinuities, signal jumps, and a high level of background noise, were reported. The aim of this work was to analyze and improve the hyperspectral output of a PHC Senop HSC-2 device by developing a general use methodology. Several signal gaps were identified as falls and jumps across the spectral signatures near 513, 650, and 930 nm, while the dark current signal magnitude and variability associated with instrumental noise showed an increasing trend over time. A data correction pipeline was successfully developed and tested, leading to 99% and 74% reductions in radiance signal jumps identified at 650 and 830 nm, respectively, while the impact of noise on the acquired signal was assessed to be in the range of 10% to 15%. The developed methodology can be effectively applied to other low-cost hyperspectral cameras.

Child-Directed Speech in Noise: Testing Signal- and Code-Based Phonetic Enhancement.

Talkers adapt their speech according to the demands of their listeners and the communicative context, enhancing the properties of the signal (pitch, intensity) and/or properties of the code (enhancement of phonemic contrasts). This study asked how mothers adapt their child-directed speech (CDS) in ways that might serve the immediate goals of increasing intelligibility, as well as long-term goals of supporting speech and language development in their children. Mothers (N = 28) participated in a real-time interactive speech production/perception paradigm, in which mothers instructed their young (3- to 5-year-old) children, or an adult listener, to select the picture corresponding to a target word. The task was performed at low and high levels (56 vs. 75 dB SPL) of background noise to examine the Lombard effects of decreased audibility on speech production. Acoustic-phonetic analyses of CDS and adult-directed speech (ADS) productions of target words and carrier phrase (e.g., "Find pig") revealed that mothers significantly enhanced the mean pitch, pitch variability, and intensity of target words in CDS, particularly at higher background noise levels and for younger children. Mothers produce CDS with a higher signal-to-noise ratio than ADS. However, limited evidence was found for phonetic enhancement of the segmental properties of speech. Although increased category separation was found in the voice onset time of stop consonants, decreased vowel category separation (an anti-enhancement effect) was observed in CDS. Mothers readily enhance the suprasegmental signal properties of their speech in CDS, but not the acoustic-phonetic properties of phonemes. This study fails to provide evidence of phonetic enhancement in preschool children in a dyadic communication task under noisy listening conditions. https://doi.org/10.23641/asha.24645423.

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro.

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. In an exploratory analysis of PBMC datasets, we find that some droplets that were originally called 'empty' due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a 'spongelet' which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.

Speech enhancement for helicopter headsets: Simulation and implementation on an FPGA platform

Clear and effective communication is crucial for the safe operation of aircraft. In helicopters, high levels of noise are generated by the engine, gears, and aerodynamics, which negatively impact speech intelligibility. To address this issue, modern aircraft headsets utilize active noise control (ANC) to reduce noise levels for both the crew and passengers. However, the speech signals captured by these headsets often contain high levels of background noise, thereby hindering internal and external flight communication. This paper introduces a dual microphone dual stage speech enhancement algorithm that combines basic spectral subtraction with a Wiener Filter, enhanced by the a priori and a posteriori signal-to-noise ratio. Audio data from within a helicopter cabin were recorded during a test flight. In a series of simulations, the Wiener Filter implementation is compared to other algorithms based only on spectral subtraction methods. The results are evaluated using established performance measures for speech quality. The Wiener Filter implementation results in the highest speech quality and is, therefore, implemented on an FPGA-platform for validation in a laboratory experiment. The simulations and measurements demonstrate significant improvements in speech quality and, consequently, enhance speech intelligibility using the proposed method.

Work-Related Vocal Challenges of Online Teaching: A Study of Female College Professors

College professors are at an elevated risk of developing voice disorders due to increased vocal demands associated with their working conditions, including high background noise levels, long reverberation times, prolonged voice use duration, and large class sizes. However, the impact of online classes on vocal health among college professors remains unclear. This longitudinal study aimed to characterize voice changes associated with online teaching among female Colombian college professors. Thirteen female college professors teaching online classes completed an online survey that included questions about voice functioning, working conditions, the Spanish translation of the Vocal Fatigue Index (VFI), and the Spanish translation of the Voice-Related Quality of Life. Instrumental measurements were also performed, including environmental background noise levels, hearing screening, and voice recordings before and after a synchronous online class. This study found a decreased fundamental frequency in connected speech (reading) associated with the number of students per class, the number of classes per week, and background noise levels measured with a sound level meter. L1L0 was statistically smaller among experienced teachers with higher background noise levels compared with less-experienced colleagues in quieter classes. 1558kHz was statistically associated with the average number of students, whereas HNR was slightly higher for professors with more students and more classes per week. The findings suggest that online teaching has important implications for voice production among participating teachers. This study highlights the importance of considering working conditions during online classes when designing workplace prevention programs for college professors.

Further application of the 1/3 oct band heavy/hard impact prediction method

Previously, the author presented a 1/3 octave band heavy/hard impact prediction method based on force pulse measurements from a drop tower. Since then, we have been applying the method with a variety of success. The previous paper was based on concrete structures in North America. This paper will be looking at the validity of the method on lighter weight mass timber buildings primarily located in the United Kingdom as well as traditional concrete buildings. The discuss will be focused on the accuracy of the method across several structures and describe why the method was less accurate in some applications. The primary cause of disagreement between predicted and in-situ measurements was high levels of background noise and other site conditions.

How Classroom Acoustic Conditions May Impact Autistic Students: A Review

Data about the prevalence of autism worldwide diverge across different censuses. However, with the growing availability of diagnostic assessments, the number of diagnosed autistic persons has been increasing over the years and, with that, also the need for accommodations. One differentiating characteristic of autistic persons compared to those who are not is a hypo- or hypersensitive response to any sensory input, usually referred to as sensory processing disorder. Here we focus on auditory hypersensitivity. In room acoustics, and more specifically in the field of classroom acoustics, it is known that the design of indoor spaces affects speech intelligibility and comprehension for people regardless of their neurological condition, which is essential in learning environments. For autistic persons, high levels of reverberation and background noise may lead to a sensory overload. This situation could be ameliorated with the use of assistive technology or adequate acoustic design. In this paper we present a literature review regarding the impacts of room acoustics on autistic people, how it can be used as an accessibility tool, and propose ideas for work to be done to better identify and resolve acoustic issues for autistic persons in classrooms.

Veterinary background noise elicits fear responses in cats while freely moving in a confined space and during an examination

Many cats show signs of fear and stress during veterinary examinations and procedures, with environmental stimuli such as noise contributing to these responses. The objective of this study was to investigate the effect of background noise commonly heard in veterinary clinics (people talking, kennel doors shutting, dogs barking) on behavioural and physiological responses in companion cats. In Experiment 1, owned cats underwent a mock physical examination in a veterinary clinic with (n = 16) or without (n = 16) a pre-recorded noise track. A second experiment was conducted to assess cat responses to noise outside of handling and a clinic environment. In Experiment 2, shelter cats were either exposed (n = 15) or not exposed (n = 15) to the same noise track while allowed free movement in a small enclosure. Physiological and behavioural responses previously validated as negative responses in cats (e.g., indicative of fear, stress and aversion) were recorded, and outcome variables were compared between treatments. For both experiments, cats exposed to the noise track showed higher heart and respiratory rates. Noise was not associated with behavioural changes during the physical examination; however, cats who were freely moving showed more behavioural signs of fear and/or stress during noise exposure compared to the no noise conditions. These results show that high levels of background noise elicit physiological stress responses in cats, while ceiling effects of the examination and exposure to the clinic environment likely prevented treatment-related behavioral differences from being detected during the physical examination. It is recommended that those working with cats in environments with high levels of background noise limit cat exposure to these noises to reduce cat fear and stress.

The use of artificial neural networks to predict tonal sound annoyance based on noise metrics and psychoacoustics parameters

The tonal noise of indoor mechanical systems causes an unpleasant sensation. The present study was conducted to predict tonal sound annoyance based on noise metrics and psychoacoustics parameters using artificial neural networks. Thirty-six signals of noise were produced by six tone levels, three tone frequencies, and two background noise levels in an enclosed space. Then, noise metrics and psychoacoustic parameters of the signals were determined. Subsequently, 60 subjects were asked to express their subjective perception of annoyance during exposure to various noises. Finally, the predictive model of annoyance was computed using the feed-forward neural networks. The initialization of weights and biases was performed using the Nguyen-Widrow method. The gradient descent with momentum and back-propagation algorithms were applied to learn the function and network weights, respectively. Based on the results, higher tone level, higher background noise level, lower frequency, and less sharp noise significantly increased the value of the perceived annoyance. The obtained Kaiser-Mayer-Olkin coefficient of the model was equal to 0.8. The values of recognition rate related to data of training and testing were computed by 0.83 and 0.91, respectively. The parameters of loudness, audible tone, and roughness compared to combined metrics were more substantial predictors of perceived annoyance.

Effects of vertical nonlinearity on the superconducting gravimeter CT #036 at Ishigakijima, Japan

One of the characteristic features of the gravity recordings produced by the superconducting gravimeter CT #036 at Ishigakijima, Japan, is that it indicates gravity increase when a typhoon (hurricane) approaches the island. Since we are trying to detect small gravity signals associated with the long-term slow slip events in this region, it is very important in the interpretation of the observed data whether such gravity changes are of natural or instrumental origin. In this paper, we investigate whether or not nonlinearity in the sensor of the superconducting gravimeter is responsible for this phenomenon. Here we take the same theoretical approach as taken by our previous study which investigated the effect of coupling between horizontal and vertical components of the gravity sensor in order to understand the noise caused by the movements of a nearby VLBI antenna. From theoretical and experimental approaches, we prove that the gravity increase observed by CT #036 at the times of high background noise level cannot be explained by instrumental effects, such as the nonlinearity in the vertical component or the coupling between horizontal and vertical components of the gravity sensor. This implies that the observed gravity increases are real gravity signals of natural origin.Graphical

Lombard effect, intelligibility, ambient noise, and willingness to spend time and money in a restaurant amongst older adults

Dining establishments are an essential part of the social experience. However, they are often characterized by high levels of background noise, which represents a barrier to effective communication. This particularly affects people suffering from hearing problems. Moreover, noise level exceeding normal conversational levels causes a phenomenon called the Lombard Effect, an involuntary tendency to increase the amount of vocal effort when talking in the presence of noise. Adults over 60 years represent the second largest population in the US and the majority of them suffer from some degree of hearing loss. The primary aim of the current study was to understand the effect of noise on vocal effort and speech intelligibility in a restaurant setting for adults over 60 years old with and without hearing loss. The secondary aim was to evaluate their perception of disturbance in communication and their willingness to spend time and money in a restaurant was affected by the varying levels of background noise. The results of this study showed background noise levels lower than 50 dB(A) will allow senior customers to minimize their vocal effort and to maximize their understanding of conversations, even for those with moderate to severe hearing loss. By setting a limit, it will also keep perceived disturbance low and willingness to spend time and money high among dining patrons.

Characterization of ground oscillations induced by underground mining

We examine ground acceleration during M1.5 and M2.0 seismic events induced by underground mining at Upper Silesian coal basin and Legnica Glogow copper mine, respectively, using methods of nonlinear time series analysis, in order to confirm its stochastic nature. Recorded time series are firstly embedded into the adequate phase space using the mutual information and box-assisted methods. After this, we performed stationarity test, by which we confirmed that the examined ground acceleration belongs to a group of stationary processes. Surrogate data testing is applied then, which resulted in following: (1) horizontal ground acceleration at Legnica Glogow copper mine represents stationary linear stochastic processes with Gaussian inputs, (2) ground acceleration at Upper Silesian coal basin originates from a stationary Gaussian linear process that has been distorted by a monotonic, instantaneous, time-independent non-linear function, (3) vertical ground acceleration at Legnica Glogow copper mine could not be ascribed to any of the examined processes, probably due to high level of instrumental or background noise. Low values of determinism coefficient (c≤0.7), negative values of maximum Lyapunov exponent and quick saturation of neighboring points distance with the increase of embedding dimension indicate the absence of determinism in the observed ground acceleration time series.

PET/CT background noise and its effect on speech recognition

Positron emission tomography (PET) has been successfully used to investigate central nervous processes, including the central auditory pathway. Unlike early water-cooled PET-scanners, novel PET/CT scanners employ air cooling and include a CT system, both of which result in higher background noise levels. In the present study, we describe the background noise generated by two state-of-the-art air-cooled PET/CT scanners. We measured speech recognition in background noise: recorded PET noise and a speech-shaped noise applied in clinical routine to subjects with normal hearing. Background noise produced by air-cooled PET/CT is considerable: 75.1 dB SPL (64.5 dB(A)) for the Philips Gemini TF64 and 76.9 dB SPL (68.4 dB(A)) for the Philips Vereos PET/CT (Philips Healthcare, The Netherlands). Subjects with normal hearing exhibited better speech recognition in recorded PET background noise compared with clinically applied speech-shaped noise. Speech recognition in both background noises correlated significantly. Background noise generated by PET/CT scanners should be considered when PET is used for the investigation of the central auditory pathway. Speech in PET noise is better than in speech-shaped noise because of the minor masking effect of the background noise of the PET/CT.

Birds of a feather speak together: Understanding the different dialects of animals can help to decipher their communication.

As humans, many animal species that communicate via vocalization show a wide range of accents and dialects driven by environmental and social factors.

Separating overlapping echolocation: An updated method for estimating the number of echolocating animals in high background noise levels.

Much can be learned by investigating the click trains of odontocetes, including estimating the number of vocalizing animals and comparing the acoustic behavior of different individuals. Analyzing such information gathered from groups of echolocating animals in a natural environment is complicated by two main factors: overlapping echolocation produced by multiple animals at the same time, and varying levels of background noise. Starkhammar et al. [(2011a). Biol. Lett. 7(6), 836-839] described an algorithm that measures and compares the frequency spectra of individual clicks to identify groups of clicks produced by different individuals. This study presents an update to this click group separation algorithm that improves performance by comparing multiple click characteristics. There is a focus on reducing error when high background noise levels cause false click detection and recordings are of a limited frequency bandwidth, making the method applicable to a wide range of existing datasets. This method was successfully tested on recordings of free-swimming foraging dolphins with both low and high natural background noise levels. The algorithm can be adjusted via user-set parameters for application to recordings with varying sampling parameters and to species of varying click characteristics, allowing for estimates of the number of echolocating animals in free-swimming groups.

Extreme ecological constraints lead to high degree of individual stereotypy in the vocal repertoire of the Cape fur seal (Arctocephalus pusillus pusillus)

The ability to recognize the identity of conspecifics is a key component for survival of many animal species and is fundamental to social interactions such as parental care, intra-sexual competition or mate recognition. In group-living species, the simultaneous co-existence of many individuals increases the number of interactions and reinforces the need for individual recognition. Acoustic signals are widely used by birds and mammals to communicate and to convey information about identity, but their use in very dense colonies becomes challenging due to the high level of background noise and the high risk of confusion among individuals. The Cape fur seal (CFS) is the most colonial pinniped species and one of the most colonial mammals in the world, with colonies of up to 210,000 individuals during the breeding season. Here, we investigated the individual stereotypy in vocalizations produced by pups, females and male CFS using Random Forests and index of vocal stereotypy (IVS). We thus compared IVS values of CFS to other pinniped species. Within CFS we identified individuality in all call types but the degree of individual stereotypy varies in regard to their social function: affiliative calls produced in a mother–pup reunion context and territorial calls produced by mature bulls holding harem were more individualized than vocalizations involved in agonistic interactions. Our inter-species comparisons among pinnipeds showed that CFS affiliative and territorial calls displayed higher degrees of individuality compared to other species with similar or lower ecological constraints (colony density and social structure). Individual recognition is primordial for the establishment of social interactions and notably occurs through acoustic signals in many birds and mammalian species. Understanding the role of social complexity in the development of individual vocal recognition improves our general knowledge on acoustic communication in a social system. This study investigated the vocal stereotypy in the Cape fur seal (CFS), a species that is an extreme illustration of social complexity. The CFS is the most colonial pinniped species, and this results in high selective pressure for individual recognition during mother–pup reunions and male territorial behaviour. By comparing the degree of individuality contained in CFS vocalizations with other pinniped species, we can assess how ecological (environmental and social) constraints drive communication systems in vertebrates.

Variation of the Acoustic Parameter Harmonic-to-noise Ratio in Relation to Different Background Noise Levels

Introduction and objectivesAcoustic analysis is a tool widely used by professionals related to the study of voice that gives us information from a recording. It has been identified that in investigations carried out today that involve acoustic analysis, the recording process takes place in rooms with different levels of background noise. The objective of this study is to establish whether the acoustic parameter, Harmonic to Noise Ratio (HNR) varies in relation to the different background noise levels of the premises where the recording is made and recommend a maximum level of background noise. MethodsThrough the Praat programme, the average value of the acoustic parameter HNR of 43 subjects was obtained, inside the audiometric booth of the Universidad Autónoma de Chile, whose background noise level is 28.1 dB (A) and it was compared with the HNR average values obtained with higher background noise levels. ResultsThe HNR average values decreased from 19.8 dB (A) to 14.0 dB (A) as the background noise level of the premises increased from 28.1 dB (A) to 57.8 dB (A). The t-test for dependent samples was performed, with which the HNR average values obtained were compared with the baseline background noise level (28.1 dB (A)). Significant differences were found with the baseline background noise level when the room noise level was higher than 47.7 dB (A). ConclusionsThe background noise of the premises where the voice recording for the acoustic analysis is performed, influences the value of the acoustic parameter HNR, which decreases as the background noise of the premises increases. It is recommended that the background noise level should not exceed 43.8 dB (A).

COVID-19 and the opportunities for research: The lockdowns' impacts on wildlife, ecology and conservation biology, and the humanities.

The ongoing lockdowns provide ideal conditions to study the relationship between wildlife and humans but among humans themselves.