Showing papers on "Background noise published in 2013"

The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings

Abstract: Multi-microphone arrays allow for the use of spatial filtering techniques that can greatly improve noise reduction and source separation. However, for speech and audio data, work on noise reduction or separation has focused primarily on one- or two-channel systems. Because of this, databases of multichannel environmental noise are not widely available. DEMAND (Diverse Environments Multi-channel Acoustic Noise Database) addresses this problem by providing a set of 16-channel noise files recorded in a variety of indoor and outdoor settings. The data was recorded using a planar microphone array consisting of four staggered rows, with the smallest distance between microphones being 5 cm and the largest being 21.8 cm. DEMAND is freely available under a Creative Commons license to encourage research into algorithms beyond the stereo setup.

Apparatus and method to classify sound to detect speech

Abstract: Audio frames are classified as either speech, non-transient background noise, or transient noise events. Probabilities of speech or transient noise event, or other metrics may be calculated to indicate confidence in classification. Frames classified as speech or noise events are not used in updating models (e.g., spectral subtraction noise estimates, silence model, background energy estimates, signal-to-noise ratio) of non-transient background noise. Frame classification affects acceptance/rejection of recognition hypothesis. Classifications and other audio related information may be determined by circuitry in a headset, and sent (e.g., wirelessly) to a separate processor-based recognition device.

New method for gravitational wave detection with atomic sensors.

Abstract: Laser frequency noise is a dominant noise background for the detection of gravitational waves using long-baseline optical interferometry. Amelioration of this noise requires near simultaneous strain measurements on more than one interferometer baseline, necessitating, for example, more than two satellites for a space-based detector or two interferometer arms for a ground-based detector. We describe a new detection strategy based on recent advances in optical atomic clocks and atom interferometry which can operate at long baselines and which is immune to laser frequency noise. Laser frequency noise is suppressed because the signal arises strictly from the light propagation time between two ensembles of atoms. This new class of sensor allows sensitive gravitational wave detection with only a single baseline. This approach also has practical applications in, for example, the development of ultrasensitive gravimeters and gravity gradiometers.

How does noise affect amplitude and latency measurement of event‐related potentials (ERPs)? A methodological critique and simulation study

Abstract: There is considerable variability in the quantification of event-related potential (ERP) amplitudes and latencies. We examined susceptibility of ERP quantification measures to incremental increases in background noise through published ERP data and simulations. Measures included mean amplitude, adaptive mean, peak amplitude, peak latency, and centroid latency. Results indicated mean amplitude was the most robust against increases in background noise. The adaptive mean measure was more biased, but represented an efficient estimator of the true ERP signal particularly for individual-subject latency variability. Strong evidence is provided against using peak amplitude. For latency measures, the peak latency measure was less biased and less efficient than the centroid latency measurement. Results emphasize the prudence in reporting the number of trials retained for averaging as well as noise estimates for groups and conditions when comparing ERPs.

Detection and classification of acoustic scenes and events: An IEEE AASP challenge

Abstract: This paper describes a newly-launched public evaluation challenge on acoustic scene classification and detection of sound events within a scene. Systems dealing with such tasks are far from exhibiting human-like performance and robustness. Undermining factors are numerous: the extreme variability of sources of interest possibly interfering, the presence of complex background noise as well as room effects like reverberation. The proposed challenge is an attempt to help the research community move forward in defining and studying the aforementioned tasks. Apart from the challenge description, this paper provides an overview of systems submitted to the challenge as well as a detailed evaluation of the results achieved by those systems.

Constructing Noise-Invariant Representations of Sound in the Auditory Pathway

Abstract: Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics. Here we investigated the extent of neuronal adaptation to the mean and contrast of auditory stimulation as one ascends the auditory pathway. We measured these forms of adaptation by presenting complex synthetic and natural sounds, recording neuronal responses in the inferior colliculus and primary fields of the auditory cortex of anaesthetized ferrets, and comparing these responses with a sophisticated model of the auditory nerve. We find that the strength of both forms of adaptation increases as one ascends the auditory pathway. To investigate whether this adaptation to stimulus statistics contributes to the construction of noise-invariant sound representations, we also presented complex, natural sounds embedded in stationary noise, and used a decoding approach to assess the noise tolerance of the neuronal population code. We find that the code for complex sounds in the periphery is affected more by the addition of noise than the cortical code. We also find that noise tolerance is correlated with adaptation to stimulus statistics, so that populations that show the strongest adaptation to stimulus statistics are also the most noise-tolerant. This suggests that the increase in adaptation to sound statistics from auditory nerve to midbrain to cortex is an important stage in the construction of noise-invariant sound representations in the higher auditory brain.

Design and Analysis of Compressed Sensing Radar Detectors

Abstract: We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements corrupted by additive white Gaussian noise. We propose two novel architectures and compare their performance by means of Receiver Operating Characteristic (ROC) curves. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP) algorithm, we characterize the statistics of the l1-norm reconstruction error and derive closed form expressions for both the detection and false alarm probabilities of both schemes. Of the two architectures, we demonstrate that the best performing one consists of a reconstruction stage based on CAMP followed by a detector. This architecture, which outperforms the l1-based detector in the ideal case of known background noise, can also be made fully adaptive by combining it with a conventional Constant False Alarm Rate (CFAR) processor. Using the state evolution framework of CAMP, we also derive Signal to Noise Ratio (SNR) maps that, together with the ROC curves, can be used to design a CS-based CFAR radar detector. Our theoretical findings are confirmed by means of both Monte Carlo simulations and experimental results.

Effect of noise on auditory processing in the operating room.

Abstract: Background Effective communication is a critical component of patient care in the operative room (OR). However, the presence of loud equipment, a large number of staff members, and music can contribute to high levels of background noise. In a setting in which crucial tasks are performed continuously, distractions and barriers to communication can result in harm to both patients and OR personnel. The purpose of this investigation was to simulate OR listening conditions and evaluate the effect of operating noise on auditory function. Study Design This is a prospective investigation of 15 subjects ranging from 1 to 30 years of operative experience. All surgeons had normal peripheral hearing sensitivity. The surgeons' ability to understand and repeat words were tested using the Speech in Noise Test–Revised in 4 different conditions chosen to simulate typical OR environments. These included quiet, filtered noise through a mask and background noise both with and without music. They were tested in both a tasked and in an untasked situation. Results It was found that the impact of noise is considerably greater when the participant is tasked. Surgeons demonstrated substantially poorer auditory performance in music than in quiet or OR noise. Performance in both conditions was poorer when the sentences were low in predictability. Conclusions Operating room noise can cause a decrease in auditory processing function, particularly in the presence of music. This becomes even more difficult when the communication involves conversations that carry critical information that is unpredictable. To avoid possible miscommunication in the OR, attempts should be made to reduce ambient noise levels.

A Multichannel MMSE-Based Framework for Speech Source Separation and Noise Reduction

Abstract: We propose a new framework for joint multichannel speech source separation and acoustic noise reduction. In this framework, we start by formulating the minimum-mean-square error (MMSE)-based solution in the context of multiple simultaneous speakers and background noise, and outline the importance of the estimation of the activities of the speakers. The latter is accurately achieved by introducing a latent variable that takes N+1 possible discrete states for a mixture of N speech signals plus additive noise. Each state characterizes the dominance of one of the N+1 signals. We determine the posterior probability of this latent variable, and show how it plays a twofold role in the MMSE-based speech enhancement. First, it allows the extraction of the second order statistics of the noise and each of the speech signals from the noisy data. These statistics are needed to formulate the multichannel Wiener-based filters (including the minimum variance distortionless response). Second, it weighs the outputs of these linear filters to shape the spectral contents of the signals' estimates following the associated target speakers' activities. We use the spatial and spectral cues contained in the multichannel recordings of the sound mixtures to compute the posterior probability of this latent variable. The spatial cue is acquired by using the normalized observation vector whose distribution is well approximated by a Gaussian-mixture-like model, while the spectral cue can be captured by using a pre-trained Gaussian mixture model for the log-spectra of speech. The parameters of the investigated models and the speakers' activities (posterior probabilities of the different states of the latent variable) are estimated via expectation maximization. Experimental results including comparisons with the well-known independent component analysis and masking are provided to demonstrate the efficiency of the proposed framework.

Using response time to speech as a measure for listening effort.

Abstract: Objective: Speech signals that do not differ in intelligibility might differ in listening effort. This study aimed to investigate the effect of background noise on response time to intelligible speech. Design: We added various amounts of stationary noise to spoken digit triplets and measured the influence of noise on the response time for both an identification and an arithmetic task: Task 1 ‘identify the final digit in a triplet’, and Task 2 ‘calculate the sum of the initial and the final digits in a triplet.’ Study sample: Twelve normal-hearing participants with a mean age of 30.6 years (range: 28–44 years). Results: Response time increased with lower (i.e. worse) signal to noise ratios for both tasks, even for signal to noise ratios with almost maximum intelligibility (close to 100%). The response time during the arithmetic task was more affected by the noise than during the identification task, but the arithmetic task demonstrated higher variance. Conclusions: The response time to digit triple...

Enhancement of SNR and Spatial Resolution in $\varphi$ -OTDR System by Using Two-Dimensional Edge Detection Method

Abstract: A two-dimensional edge detection method has been proposed to extract location information of intruder in the distributed vibration sensing system based on phase-sensitive optical time domain reflectometry. The edge detection method is used to calculate the spatial gradient of the image composed by Rayleigh traces at each point by convolving with Sobel operator, hence the amplitude fluctuation of Rayleigh backscattering traces induced by external vibration can be located. The signal to noise ratio of location information based on the method increases to as high as 8.4 dB compared to conventional method, where the effects of noise are reduced by local averaging within the neighborhood of mask. The spatial resolution could be also optimized from 5 m to ~3 m when 50 ns pulse is launched into the single mode fiber with 1 Km length. The sensing system has the potential to extract available signals from the hostile environments with strong background noise.

Acoustic Environment Identification and Its Applications to Audio Forensics

Abstract: An audio recording is subject to a number of possible distortions and artifacts. Consider, for example, artifacts due to acoustic reverberation and background noise. The acoustic reverberation depends on the shape and the composition of a room, and it causes temporal and spectral smearing of the recorded sound. The background noise, on the other hand, depends on the secondary audio source activities present in the evidentiary recording. Extraction of acoustic cues from an audio recording is an important but challenging task. Temporal changes in the estimated reverberation and background noise can be used for dynamic acoustic environment identification (AEI), audio forensics, and ballistic settings. We describe a statistical technique to model and estimate the amount of reverberation and background noise variance in an audio recording. An energy-based voice activity detection method is proposed for automatic decaying-tail-selection from an audio recording. Effectiveness of the proposed method is tested using a data set consisting of speech recordings. The performance of the proposed method is also evaluated for both speaker-dependent and speaker-independent scenarios.

Silver and Chan revisited

Abstract: [1] Seismic shear waves emitted by earthquakes can be modeled as plane (transverse) waves. When entering an anisotropic medium, they can be split into two orthogonal components moving at different speeds. This splitting occurs along an axis, the fast polarization, that is determined by geologic conditions. We present here a comprehensive analysis of the Silver and Chan (1991) method, used to obtain shear wave splitting parameters, comprising theoretical derivations and statistical tests of the assumptions used to construct the standard errors. We find discrepancies in the derivations of equations in their article, with the most important being a mistake in how the standard errors are calculated. Our simulations suggest that the degrees of freedom are being overestimated by this method, and consequently, the standard errors are too small. Using a set of S waveforms from very similar shallow earthquakes on Reunion Island, we perform a statistical analysis on the noise of these replicates and find that the assumption of Gaussian noise does not hold. Further, the properties of background noise differ substantially from the noise obtained from the shear wave splitting analysis. However, we find that the estimated standard errors for the fast polarization are comparable to the spread in the fast polarization parameters between events. Delay time errors appear to be comparable to delay time estimates once cycle skipping is accounted for. Future work using synthetic seismograms with simulated noise should be conducted to confirm this is the case for earthquakes in general.

On Optimal Linear Filtering of Speech for Near-End Listening Enhancement

Abstract: In this letter the focus is on linear filtering of speech before degradation due to additive background noise. The goal is to design the filter such that the speech intelligibility index (SII) is maximized when the speech is played back in a known noisy environment. Moreover, a power constraint is taken into account to prevent uncomfortable playback levels and deal with loudspeaker constraints. Previous methods use linear approximations of the SII in order to find a closed-form solution. However, as we show, these linear approximations introduce errors in low SNR regions and are therefore suboptimal. In this work we propose a nonlinear approximation of the SII which is accurate for all SNRs. Experiments show large intelligibility improvements with the proposed method over the unprocessed noisy speech and better performance than one state-of-the art method.

Small Hot Jet Acoustic Rig Validation

Abstract: The Small Hot Jet Acoustic Rig (SHJAR), located in the Aeroacoustic Propulsion Laboratory (AAPL) at the NASA Glenn Research Center in Cleveland, Ohio, was commissioned in 2001 to test jet noise reduction concepts at low technology readiness levels (TRL 1-3) and develop advanced measurement techniques. The first series of tests on the SHJAR were designed to prove its capabilities and establish the quality of the jet noise data produced. Towards this goal, a methodology was employed dividing all noise sources into three categories: background noise, jet noise, and rig noise. Background noise was directly measured. Jet noise and rig noise were separated by using the distance and velocity scaling properties of jet noise. Effectively, any noise source that did not follow these rules of jet noise was labeled as rig noise. This method led to the identification of a high frequency noise source related to the Reynolds number. Experiments using boundary layer treatment and hot wire probes documented this noise source and its removal, allowing clean testing of low Reynolds number jets. Other tests performed characterized the amplitude and frequency of the valve noise, confirmed the location of the acoustic far field, and documented the background noise levels under several conditions. Finally, a full set of baseline data was acquired. This paper contains the methodology and test results used to verify the quality of the SHJAR rig.

Acoustical and perceptual assessment of water sounds and their use over road traffic noise.

Abstract: This paper examines physical and perceptual properties of water sounds generated by small to medium sized water features that have applications for road traffic noise masking. A large variety of water sounds were produced in the laboratory by varying design parameters. Analysis showed that estimations can be made on how these parameters affect sound pressure levels, frequency content, and psychoacoustic properties. Comparisons with road traffic noise showed that there is a mismatch between the frequency responses of traffic noise and water sounds, with the exception of waterfalls with high flow rates, which can generate large low frequency levels comparable to traffic noise. Perceptual assessments were carried out in the context of peacefulness and relaxation, where both water sounds and noise from dense road traffic were audible. Results showed that water sounds should be similar or not less than 3 dB below the road traffic noise level (confirming previous research), and that stream sounds tend to be preferred to fountain sounds, which are in turn preferred to waterfall sounds. Analysis made on groups of sounds also indicated that low sharpness and large temporal variations were preferred on average, although no acoustical or psychoacoustical parameter correlated well with the individual sound preferences.

Mitigation of Optical Background Noise in Light-Emitting Diode (LED) Optical Wireless Communication Systems

Abstract: One challenge faced by the in-home light-emitting diode (LED) optical wireless communication is the optical noises. Here, we first experimentally characterize the effect of optical background noise to the performance of the LED optical wireless communication channel. We demonstrate using Manchester coding for the LED to mitigate the optical noise. No adaptive monitoring, feedback, or optical filtering is required. The theoretical and numerical analysis of Manchester decoding process to mitigate the optical background noise is provided. Our experimental result shows that Manchester coding can significantly eliminate optical noise generated by the AC-LED operated at <; 500 kHz and fluorescent light.

Handbook of Engineering Acoustics

Abstract: Fundamentals.- Acoustic Measurements.- Numerical Acoustics.- The Effects of Sound on Humans.- Noise Immission Assessment.- Noise Emission Assessment.- Sound propagation in the Open Space.- Building Acoustics.- Sound Absorption.- Structure Borne Sound.- Room Acoustics.- Silencers.- Active Noise and Vibration Control.- Noise caused by Construction Work.- Sound Sources.- Traffic Noise - Road.- Traffic Noise and Vibrations - Railway.- Traffic Noise - Aircraft.- Sound Reinforcement Techniques.- Urban Noise Protection.- Flow-Induced Noise.- Ultrasound.- Vibrations.- Index.

Sources of background noise and their influence on vertebrate acoustic communication

Abstract: Many animals rely on long-range communication for species recognition, mate selection and territorial defense, but background noise from the environment can constrain their communication. Background noise from both biotic and abiotic sources is ubiquitous. In general, acoustic noise from abiotic sources, including anthropogenic noise, has energy mostly below 1 kHz. Arthropods tend to produce sounds in the 4–10 kHz range, while birds, amphibians and mammals generally have vocalizations with frequencies between 1 and 5 kHz. There are several ways that signalers could improve the efficiency of their acoustic signals to counteract the constraints of background noise. Signalers could make long-term and short-term signal adjustments to increase the detectability and discriminability of their signals. As predicted by signal detection theory adjustments can include increases in contrast between signals and noise, such as the intensity of the signal, the structure of the signal and an increase in signal redundancy. Our study reviews the sources of acoustic background noise, adjustments made by signalers to increase signal efficacy, and the influence of acoustic background noise on the evolution of acoustic communication in terrestrial vertebrate species.

Audio Recording Location Identification Using Acoustic Environment Signature

Abstract: An audio recording is subject to a number of possible distortions and artifacts. Consider, for example, artifacts due to acoustic reverberation and background noise. The acoustic reverberation depends on the shape and the composition of the room, and it causes temporal and spectral smearing of the recorded sound. The background noise, on the other hand, depends on the secondary audio source activities present in the evidentiary recording. Extraction of acoustic cues from an audio recording is an important but challenging task. Temporal changes in the estimated reverberation and background noise can be used for dynamic acoustic environment identification (AEI), audio forensics, and ballistic settings. We describe a statistical technique based on spectral subtraction to estimate the amount of reverberation and nonlinear filtering based on particle filtering to estimate the background noise. The effectiveness of the proposed method is tested using a data set consisting of speech recordings of two human speakers (one male and one female) made in eight acoustic environments using four commercial grade microphones. Performance of the proposed method is evaluated for various experimental settings such as microphone independent, semi- and full-blind AEI, and robustness to MP3 compression. Performance of the proposed framework is also evaluated using Temporal Derivative-based Spectrum and Mel-Cepstrum (TDSM)-based features. Experimental results show that the proposed method improves AEI performance compared with the direct method (i.e., feature vector is extracted from the audio recording directly). In addition, experimental results also show that the proposed scheme is robust to MP3 compression attack.

Motion-blurred star acquisition method of the star tracker under high dynamic conditions

Abstract: The star tracker is one of the most promising attitude measurement devices used in spacecraft due to its extremely high accuracy. However, high dynamic performance is still one of its constraints. Smearing appears, making it more difficult to distinguish the energy dispersive star point from the noise. An effective star acquisition approach for motion-blurred star image is proposed in this work. The correlation filter and mathematical morphology algorithm is combined to enhance the signal energy and evaluate slowly varying background noise. The star point can be separated from most types of noise in this manner, making extraction and recognition easier. Partial image differentiation is then utilized to obtain the motion parameters from only one image of the star tracker based on the above process. Considering the motion model, the reference window is adopted to perform centroid determination. Star acquisition results of real on-orbit star images and laboratory validation experiments demonstrate that the method described in this work is effective and the dynamic performance of the star tracker could be improved along with more identified stars and guaranteed position accuracy of the star point.

A Robust Polynomial Filtering Framework for Mammographic Image Enhancement From Biomedical Sensors

Abstract: This paper presents a non-linear framework employing a robust polynomial filter for accomplishing enhancement of mammographic abnormalities outcoming from biomedical instrumentation, i.e., X-rays instrumentation. The approach proposed in this paper uses a linear combination of Type-0 and Type-II polynomial filters as a generalized filtering solution to achieve enhancement of mammographic masses and calcifications irrespective of the nature of background tissues. A Type-0 filter provides contrast enhancement, suppressing the ill-effects of background noise. On the other hand, Type-II filter performs edge enhancement leading to preservation of finer details. Contrast improvement index is used as a performance measure to quantify the degree of improvement in contrast of the region-of interest. In addition, estimation of signal-to-noise ratio (in terms of PSNR and ASNR) is carried out to account for the suppression in background noise levels and over-enhancements of the processed mammograms. These measures are used as a mechanism to optimally select the filter parameters and also serve as a quantifying platform to compare the performance of the proposed filter with other non-linear enhancement techniques to be used for diverse biomedical image sensors.

Masking by Noise in Acoustic Insects: Problems and Solutions

Abstract: In most environments, acoustic signals of insects are a source of high background noise levels for many birds and mammals, but at the same time, their own communication channel is noisy due to conspecific and heterospecific signalers as well. In this chapter, I first demonstrate how this situation influences communication and the evolution of related traits at the population level. Solutions for communicating under noise differ between insect taxa, because their hearing system evolved independently many times, and the signals vary strongly in the time and frequency domain. After describing some solutions from the senders’ point of view the focus of the chapter is on properties of the sensory and central nervous system, and how these properties enable receivers to detect relevant acoustic events from irrelevant noise, and to discriminate between signal variants.

Application of a recently introduced index for acoustic complexity to an avian soundscape with traffic noise.

Abstract: An altered acoustic environment can have severe consequences for natural communities, especially for species that use acoustic signals to communicate and achieve breeding success. Numerous studies have focused on traffic noise disturbance, but the possible causes of road effects are inter-correlated and the literature on noise qua noise is sometimes contradictory. To provide further empirical data in this regard, the authors investigated the spatio-temporal variability of the singing dynamics of an avian community living in an acoustic context altered by traffic noise. Fieldwork was carried out in a wood of Turkey oaks (central Italy) bordered on one side by a main road. The soundscape was examined by positioning eight digital recorders, distributed in two transects perpendicular to the road, and recording between 6:30 and 8.30 a.m. for 12 continuous sessions. The acoustic complexity index was used to obtain a quantification of singing dynamics, which were positively correlated with traffic noise. This may indicate that birds try to propagate their signals with greater emphasis (e.g., amplified redundancy or loudness of the songs) to override the masking effect of noise. Nevertheless, an ecotonal effect could have influenced the correlation results, with this enhanced dynamic possibly being due to a more densely populated environment.

Speech recognition in natural background noise.

Abstract: In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR). Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A), reference at 1 meter) at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (−8.8 dB to −18.4 dB). Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda). Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for future studies.

FAIR: A Fast Algorithm for Document Image Restoration

Abstract: We present, in this paper, the FAIR algorithm: a fast algorithm for document image restoration. This algorithm has been submitted to different contests where it showed good performance in comparison to the state of the art. In addition, this method is scale invariant and fast enough to be used in real-time applications. The method is based on a double-threshold edge detection approach that makes it possible to detect small details while remaining robust against noise. The performance of the proposition is evaluated on several types of degraded document images where considerable background noise or variation in contrast and illumination exist.

Effects of Noise on Sound Detection and Acoustic Communication in Fishes

Abstract: The ambient noise in aquatic habitats is characterized by a large variety of noise levels and spectral profiles due to various abiotic and biotic factors such as running water, wind, tides, and vocalizing animals. Fish hearing sensitivity declines when exposed to high noise levels or in the presence of masking noise, in particular, in taxa possessing hearing enhancements. Most vocal fishes communicate over short distances (<0.5 m), probably because of low sound levels produced, low sound frequencies and the ambient noise conditions. Some species exploit ‘quiet windows’ of low spectral noise levels for acoustic communication. Human-made noise such as ship noise masks the hearing abilities of fishes and hinders acoustic communication. Whether fishes are able to cope with anthropogenic noise by increasing sound amplitude, shifting dominant frequencies of sounds, or by other mechanisms remains unknown.