Ambient Sound Research Articles

An Assessment of Environmental RF Noise Due to IoT Deployment.

The advent of the Internet of Things (IoT) has contributed to an increase in the production volume of RF-featured equipment. According to statistics from the literature, the IoT industry will soon deploy billions of products. While the concept behind these applications seems exciting, this paper sought to assess the effects the radio emissions produced by IoT products would have on the ambient radio noise levels within the unlicensed frequency bands of 433 MHz, 868 MHz, and 2.4 GHz. The study extended to three environments: industrial, urban, and suburban. This study developed an IoT noise generator (ING) device to emulate RF noise signals in the desired IoT radio transmission band. The paper presents a simplified radio noise surveying system (RNSS) for data collection of ambient radio noise from five South African candidate sites. The statistical and empirical analysis agree that the level of ambient radio noise was directly proportional to the rate of IoT radio activities. The slopes of the regression lines demonstrate that 80% of the analyzed data developed augmenting trends. Approximately 20% of the data show declining trends.

Evaluation of passive acoustic methods for ambient noise baseline and gas flow rate quantification at a proposed nearshore carbon capture and storage site in Australia

Measurement, monitoring, and verification (MMV) is an integral component of carbon capture and storage (CCS) projects, providing valuable feedback for management practices and assuring integrity. Within an operational MMV equipment, hydrophone-based passive acoustic techniques are used to establish ambient noise baseline and flow rate quantification at short range, specifically to facilitate ‘detect-attribute-quantify’ sequence of an MMV program. But nearshore environments are acoustically complex with overlapping components of biophony, geophony, anthropophony, and deployment noise resulting from multiple instruments used for MMV. These soundscape components can disproportionately dominate ambient noise levels, potentially masking acoustic signatures of bubbles used to quantify seabed gas seeps. Therefore, a robust baseline describing ambient noise variability across the range of frequencies associated with acoustic emissions of gas seeps is required, from which changes can be detected and monitored. In this context, multi-year hydrophone measurements (20 Hz to 24 kHz) from a proposed nearshore CCS site in Australia are analysed to establish a temporally resolved baseline, identifying key drivers causing overall ambient noise variability. These results are compared with acoustic bubble spectrum features and flow rate estimates from a controlled in situ gas release experiment. The experiment was performed using a custom-made bubble generator at 1, 10, and 25 m range from the hydrophone to understand the likelihood of detecting bubbles and quantifying flow rate at the proposed CCS site. Despite the complexities of nearshore environment, the evaluation highlights that low-cost hydrophone-based passive acoustic methods can provide a practical solution to complement quantification component of operational MMV programs.

Monitoring of Local Earthquakes in Haiti Using Low-Cost, Citizen-Hosted Seismometers and Regional Broadband Stations

Abstract Seismic monitoring in Haiti is currently provided by a mixed network of low-cost Raspberry Shake (RS) seismic stations hosted by citizens, and short-period and broadband stations located mainly in neighboring countries. The level of earthquake detection is constantly improving for a better spatio-temporal distribution of seismicity as the number of RS increases. In this article, we analyze the impact of the quality of the signals recorded by the RS—low-cost seismometers with the smallest magnitude that the network can detect by studying the ambient noise level at these stations. Because the RS stations are installed as part of a citizen-science project, their ambient noise estimated by the power spectral density (PSD) method often shows a high-noise level at frequencies above 1 Hz. In the near field (<50 km), we show that the network detects seismic events of local magnitude on the order of 2.2 with signal-to-noise ratios (SNRs) greater than 4. Improving the network detection threshold requires densifying the network with more RS stations in locations that are less noisy, if possible. In spite of these limitations, this mixed network has provided near-field data essential to rapidly understand the mechanism of the mainshock of the 14 August 2021 Mw 7.2 earthquake, to monitor its sequence of aftershocks in near-real time, and to monitor background seismicity in Haiti on a routine basis.

Neo-liberal Transgressions in the Contemporary Film Industry: Classical Music and Dehumanised Musical Bodies in the Films The Perfection (2018) and Nocturne (2020)

The aim of this paper is to examine what I call “dehumanised musical bodies” in the psychological horror films The Perfection and Nocturne. These multi-deficient neo-liberal bodies are exposed to the stereotypical, strikingly negative image of the sophisticated world of art. Particular attention is paid to the provocative treatment of classical music, focusing on the non-normative institutional practices and ethical reconfiguration of their representatives. A strikingly raw form of musical dehumanisation is found in the film The Perfection, whose soundtrack combines ambient sounds of terror and popular tunes with great classical works by Handel, Mozart and Casadesus. The film Nocturne, on the other hand, offers a more contemplative audio-visual aesthetic with a deceptive hierarchisation of the classical music repertoire. Mozart’s music is frivolously devalued, while Saint-Saëns’ “Piano Concerto No. 2 in G Minor” is used as a narrative device for a destructive manifestation of power that leads to an avalanche of conflict between the sisters. Such explicit play with the classical music signifiers drastically deviates from conventional musical protocols and leads to alienation and, ultimately, transgressive neo-liberal dehumanisation of contemporary musicians.

Acoustic Characterization around the CalWave Wave Energy Converter

Sound generated by marine energy (ME) installations in the ocean environment remains a particular concern for environmental permitting despite the limited evidence showing low levels of ME sounds relative to other anthropogenic sounds. In an effort to increase understanding of potential environmental effects of marine energy projects and help reduce barriers to marine energy deployments, a new acoustic monitoring technology, the NoiseSpotter®, was developed and recently demonstrated around CalWave’s operational scaled xWave™ wave energy converter (WEC). The NoiseSpotter® improves upon traditional acoustic sensing techniques by use of a cost-effective, compact array of acoustic particle velocity sensors that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds in real time. Results are presented from co-deployments of NoiseSpotter® with the operational CalWave WEC that were conducted over a 9-day period in fall 2021 offshore of Scripps Research Pier in San Diego, California, USA. The multi-day deployment of the NoiseSpotter® at 100 m from the CalWave WEC revealed a rich library of sounds that include: Low-level (~95 dB re 1 µPa relative to an ambient noise floor between 80-90 dB re 1 µPa) sounds from the WEC associated with the deliberate actuation of mechanical components, Sounds from a hovering helicopter, Marine mammal vocalizations, and, Small boat engines. Sound levels from the WEC were placed within the context of ambient sounds, and reveal little deviation from the ambient soundscape. The azimuthal anisotropy of WEC sound was investigated via deployments along four cardinal directions around the WEC. While a noticeable increase was observed along the north-south orientation, the sound levels along all directions still showed little deviation relative to the ambient noise floor. Analysis of low-level WEC sounds in conjunction with exploratory machine learning techniques demonstrate the utility of directional acoustic sensing in distinguishing marine energy sounds from the myriad other sounds in the surrounding ocean environment.

Ambient noise levels with depth from an underwater glider survey across shipping lanes in the Gulf of St. Lawrence, Canada.

A two-month-long glider deployment in the Gulf of St. Lawrence, Canada, measured the ambient sound level variability with depth and lateral position across a narrow channel that serves as an active commercial shipping corridor. The Honguedo Strait between the Gaspé Peninsula and Anticosti Island has a characteristic sound channel during the Summer and Fall due to temperature variation with depth. The experiment comprised continuous acoustic measurements in the band 1-1000 Hz and oceanographic (temperature and salinity) measurements from a profiling electric glider down to 210 m water depth. The mean observed ambient sound depth-profile was modeled by placing a uniform distribution of sources near the surface to represent a homogeneous wind-generated ocean wave field and computing the acoustic field using normal modes. The measurements and predictions match within the observed error bars and indicate a minimum in the sound channel at 70 m depth and a relative increase by ∼1 dB down to 180 m depth for frequencies >100 Hz. The impact of detector depth, the distance to a busy shipping corridor, wind noise, flow noise, and self-noise are discussed in the context of passive acoustic monitoring and marine mammal detection.

Voice user interfaces in manufacturing logistics: a literature review

AbstractDue to the increasing digitalization in manufacturing logistics, devices to integrate the worker into the digital manufacturing system are necessary. A voice user interface (VUI) can be considered suitable for this purpose due to its flexibility and intuitive operability. Despite the popularity and acceptance of VUIs in everyday life, their use in industrial applications, especially in manufacturing logistics, is still rare. While VUIs have been successfully used in order picking for decades, hardly any other industrial fields of application exist. In this paper, we have identified various barriers to the use of VUI in industrial applications. We categorized them and identified four key barriers. We then conducted a systematic literature review to determine and compare already investigated application areas of VUIs, their characteristics, advantages and disadvantages. We found that in particular the operation of machines and industrial robots, as well as general data and information output on machine and system status, maintenance and employee training are frequently investigated. It is noticeable that VUIs are often used in combination with other user interfaces (UIs). Some challenges to VUI usage, such as high ambient noise levels, have already been solved through various approaches, while other challenges remain. Based on the results of the literature review, we put forward a research agenda regarding further suitable industrial application areas as well as general challenges for the use of VUIs in industrial environments.

DESIGNING HORROR SURVIVAL MYSTERY GAME ”REMEMBER THE DAYS” COMBINING 2D AND 3D ELEMENTS.

“Remember The Days” is a survival horror single player game for Windows, that combines 2D and 3D elements with a pixelated and low poly art style. As a detective trapped in an old abandoned haunted house, players must solve puzzles, and be able to manage limited resources to survive and escape. The game’s immersive storytelling is told through environmental cues and artifacts, complemented by a haunting soundtrack and ambient sounds that add to the eerie atmosphere. This game will bring a spine-tingling horror experience of exploration, puzzle solving, and survival. The game will be develop using Unity Engine and C as the main programming language.

Analysis of Regional Ambient Seismic Noise in the Chukchi Sea Area in the Arctic Based on OBS Data from the Ninth Chinese National Arctic Scientific Survey

Ambient noise plays a crucial role in influencing the observation quality at seismic stations. By studying the distribution patterns of ambient noise, we can gain initial insights into the noise conditions within a specific research area. This paper investigates the properties of ambient noise in different frequency bands under environmental settings in the Chukchi Sea region, utilizing data collected from ocean bottom seismometers (OBSs) deployed during the Ninth Chinese National Arctic Scientific Survey. The probability density function (PDF) method is used to reveal the distinctive features of ambient noise. In addition, by comparing the crowed number values of ambient noise in the Chukchi Sea area with the global new low-noise model (NLNM) and new high-noise model (NHNM), a more comprehensive understanding of the patterns, distribution characteristics, and sources of ambient noise in the Arctic Chukchi Sea area is gained. The study suggests that the overlying sea ice in the Arctic Chukchi Sea area can suppress the microseismic band ambient noise, and the overall level of ambient noise in the Chukchi Sea area lies between the land seismic ambient noise level and the ambient noise level in the middle- and low-latitude sea areas. Meanwhile, an abnormal power spectrum caused by different levels of natural earthquakes is observed. This study fills the gap by using seafloor seismic instruments to investigate ambient noise in the Chukchi Sea area.

Detection of Rain in Tropical Cyclones by Underwater Ambient Sound

Abstract Rain in tropical cyclones is studied using eight time series of underwater ambient sound at 40–50 kHz with wind speeds up to 45 m s−1 beneath three tropical cyclones. At tropical cyclone wind speeds, rain- and wind-generated sound levels are comparable, and therefore rain cannot be detected by sound level alone. A rain detection algorithm that is based on the variations of 5–30-kHz sound levels with periods longer than 20 s and shorter than 30 min is proposed. Faster fluctuations (<20 s) are primarily due to wave breaking, and slower ones (>30 min) are due to overall wind variations. Higher-frequency sound (>30 kHz) is strongly attenuated by bubble clouds. This approach is supported by observations that, for wind speeds < 40 m s−1, the variation in sound level is much larger than that expected from observed wind variations and is roughly comparable to that expected from rain variations. The hydrophone results are consistent with rain estimates by the Tropical Rainfall Measuring Mission (TRMM) satellite and with Stepped-Frequency Microwave Radiometer (SFMR) and radar estimates by surveillance flights. The observations indicate that the rain-generated sound fluctuations have broadband acoustic spectra centered around 10 kHz. Acoustically detected rain events usually last for a few minutes. The data used in this study are insufficient to produce useful estimation of rain rate from ambient sound because of limited quantity and accuracy of the validation data. The frequency dependence of sound variations suggests that quantitative rainfall algorithms from ambient sound may be developed using multiple sound frequencies. Significance Statement Rain is an indispensable process in forecasting the intensity and path of tropical cyclones. However, its role in the air–sea interaction is still poorly understood, and its parameterization in numerical models is still in development. In this work, we analyzed sound measurements made by hydrophones on board Lagrangian floats beneath tropical cyclones. We find that wind, rain, and breaking waves each have distinctive signatures in underwater ambient sound. We suggest that the air–sea dynamic processes in tropical cyclones can be explored by listening to ambient sound using hydrophones beneath the sea surface.

Effects of anthropogenic noise and natural soundscape on larval fish behavior in four estuarine species.

The larval and post-larval forms of many marine organisms, such as oysters, crabs, lobster, coral, and fish, utilize ambient acoustic cues to orient, settle, or metamorphose. In this study, the effect of anthropogenic and ambient sounds on the orientation behavior of four larval estuarine fishes was examined in a controlled, laboratory experiment. Pre-settlement size red drum Sciaenops ocellatus, southern flounder Paralichthys lethostigma, spotted seatrout Cynoscion nebulosus, and Florida blenny Chasmodes saburrae larvae were exposed to four sound treatments-control, estuarine soundscape, seismic airguns, and large-ship passage-in a linear acoustic chamber. Initial significant (p < 0.05) avoidance of airguns was observed in three of the four species (all but the Florida blenny), but habituation to this sound occurred as the experiment progressed. All species avoided ship passage sounds; however, the avoidance behavior was not significant. Interestingly, none of the species studied were significantly attracted to the acoustic cues alone of the estuarine soundscape; in fact, three of the four species spent less time near the speaker when it was broadcast. These results suggest that larval fish can potentially habituate to anthropogenic noise relatively quickly (<10 min). Understanding how sounds affect larval behavior is necessary because successful recruitment ultimately affects a population's success.

Key Agreement on IoT Devices With Echo Profiling

Secure Device-to-Device (D2D) communication is important for the Internet-of-Things (IoT) devices. Key agreement between devices is the important first step in building a secure D2D channel. Due to the lack of third-party certification, key agreement for IoT devices has to rely on the untrusted channel between them, which makes the pairing process vulnerable to attacks such as eavesdropping, jamming, and predictable channel attack. We solve this problem with a novel key agreement method named, where two nearby devices can generate a symmetric key independently, leveraging the ambient sound signal that can be locally collected by devices. The intuition of this idea is that the propagation delays of the ambient sounds and the echoes will carry fine-grained information about the spatial context of the receiving device, which can be transformed to a special key for that device. So, nearby devices which have similar spatial context will generate similar echo profiles. We implement a prototype of and evaluate its performance in resisting different attacks. The results tell that, with, the key agreement process is even undetectable by an attacker which is only 50cm away from the pairing devices, and is thus resistant to all attacks mentioned above.

Influence of Overpressure Breathing on Vowel Formant Frequencies

Voice controlled management systems are based on speech recognition techniques. The use of such systems in combat aircraft is complex due to a number of critical factors which affect the accuracy of speech recognition, such as high level of ambient noise and vibration, use of oxygen masks, serious psycho-physical stress of speakers, etc. One of the specificity of the oxygen mask application is overpressure breathing. The results of the simulations presented in this paper show that the presence of overpressure on the order of 1000 Pa in the vocal tract has a significant influence on the first two formant frequencies. The formants discrimination field is significantly reduced when oxygen mask is used, influencing both perceptive and automatic discrimination of spoken vowels.

Alternative audiometric calibration methods: Evaluation of sound level measuring apps for audiometric calibration

Audiometric calibration, which includes the calibration of different audiometer transducers and the measurements of ambient noise levels, is historically carried out using Class 1 sound level meters. As technologies advance, many mobile applications (apps) have been developed to measure sound levels. These apps can provide alternative methods for audiometric calibration in places where sound level meters are not available, such as field testing environments, low-to-mid-income countries, and humanitarian settings. These apps, however, cannot be used for audiometric calibration without first evaluating their performance, which depends on multiple factors including the external components (if any), the operating system and the hardware of the electronic devices. The evaluation of the apps is actually the evaluation of the app and associated factors (i.e., the app systems). This paper discusses methods to assess several key functions of apps implemented in either Android or iOS operation system for audiometric calibration: 1) checking the measurement accuracy at all testing frequencies, 2) deriving and using correction factors, 3) determining the self-noise levels, and 4) evaluating the linear/measurement range. As audiometric calibration usually uses octave or 1/3 octave bands to measure sound pressure levels of tones and narrowband noises with relatively steady temporal characteristics, the accuracy of an app can be evaluated by comparing the levels measured by the app and a Class 1 sound level meter at each frequency. The level difference between the app and the Class 1 sound level meter at each frequency can then be used to calculate correction factors that can be added to subsequent levels measured by the app to improve its accuracy. In addition, methods to determine the self-noise level and the linearity range of apps are discussed. Sample measurement scenarios and alternative methods are provided to illustrate the evaluation process to determine whether an app is suitable for measuring ambient noise levels and for calibrating different audiometric transducers.

The New York Misophonia Scale (NYMS): A New Instrument to Identify Misophonia in the General Population.

Misophonia is a condition in which certain sounds and behaviors elicit distress that ranges from mild annoyance to disgust or anger. The aim of this research was to develop and validate an instrument to screen for misophonia in the general population. Study 1 developed and explored the factor structure and item quality of the New York Misophonia Scale (NYMS), which originally included 42 triggers and 13 behavioral reactions. A sample of 441 American adults responded to the instrument via social media platforms. Of the original 42 triggers, 25 clustered into 4 factors: repetitive actions, mouth sounds, ambient object sounds, and ambient people sounds. The 13 behavioral reactions loaded on to 2 factors, aggressive and nonaggressive reactions. Study 2 evaluated the psychometric properties of the final version of the NYMS using a sample of 200 American adults. The results supported the validity of the factor structure and the reliability of the final version of the NYMS from Study 1. Finally, Study 3 explored the concurrent and convergent validity of the final version of the NYMS with the Misophonia Questionnaire (MQ) and the Difficulties in Emotion Regulation Scale-Short Form (DERS-SF). A sample of 171 adult participants completed all of the scales. Good concurrent validity was found with the MQ and good convergent validity was found with the DERS-SF. Overall, the NYMS appears to be a useful and promising instrument for assessing misophonia triggers, severity of distress elicited, and behavioral reactions to the distress in the general population.

Monitoring induced microseismicity in an urban context using very small seismic arrays: The case study of the Vendenheim EGS project

Monitoring the seismicity induced by fluid injections in deep geothermal reservoirs is often limited by the significant anthropogenic ambient noise level inherent to most enhanced geothermal system (EGS) projects in urban contexts. We report on the performance of a monitoring network made of three small aperture (72 m) seismic arrays composed of 21 3D nodes. We test the setup for four months (from 12 December 2020 to 8 April 2021) of the Strasbourg sequence of induced earthquakes (2019–2022) related to the EGS Georhin project (Vendenheim, France). The deployment starts a few days after the MLv = 3.6 induced earthquake of 4 December 2020 and covers the early shut-in period of the wells. We use a beamforming technique to characterize the main noise sources, which consist of slow apparent velocities of surface waves emitted from mobile anthropogenic sources (motorway and railway traffic). We detect events with a phase-weighted stacking method, which is efficient when wavefronts illuminate the arrays with a high apparent velocity. Earthquakes associated with these detections are located using a matched field processing technique. The obtained catalog includes 216 seismic events, which represent four times more events than the reference catalog from Le Bureau Central Sismologique Français–Renass (the national academic agency in charge of seismicity monitoring in France), and a reduction of the completeness magnitude from 0.3 to −0.5. The clustering of the seismicity is analyzed using waveform correlation. The enriched catalog reveals intermittent seismic activity during the slow and continuous decrease in fluid pressure after shut-in.

0935 An Investigation of ICU Ambient Noise Levels as a Potential Source for Poor Sleep Outcomes in a Community Hospital Setting

Abstract Introduction Patients in the intensive care unit (ICU) are subject to multiple necessary diagnostic and therapeutic interventions throughout the course of their treatment that contribute to sleep deprivation. These measures increase ambient noise, impacting patient morbidity and mortality by exacerbating confusion, ICU-related delirium, recovery time, and long term sequelae associated with Post-Intensive Care Syndrome. The World Health Organization suggests critically-ill patients not exceed exposure to sound levels higher than 35-40 decibels (dB). In this study, we measured ICU sound levels in a community hospital setting to support intervention with conservative bundle measures or behavior modification with a visual noise monitoring device. Methods This study took place over two months (October-November, 2021) in the critical care unit of St Agnes Medical Center in Fresno, CA. Ambient noise was monitored using a sound decibel meter (Gain Express Holdings, SLM-25) connected to recording software that measured the decibel levels at 1-minute intervals for 24 hours in three areas: two central stations (Station A and B) and one occupied patient room, equidistant to both central stations. The monitor data was exported to Microsoft Excel (2020 version; Microsoft Corp, Redmond, WA, USA) for analysis. Data from each sample was expressed as M±SE (95% confidence interval). Results Both central stations had average levels of 44.1dB± 4.7 and 48.0dB± 4.3, with a frequency range of 40-50 dB greater than 50% of the time. Station A had a frequency range of 50-60 dB approximately 11% of the time and Station B at 30% of the time. The occupied patient room had average levels of 48.0dB± 5.4, with frequency of 40-50 dB greater than 50%, and levels 50-60 dB greater than 30% of the time. Conclusion ICU’s with higher than recommended ambient sound levels may benefit from appropriate intervention such as visual noise monitoring devices or order-sets with protocols on equipment/staff phone volume, earplugs for patients, and limiting staff conversation to distances away from the bedside. Support (if any)

A Mobile Sensing Framework for Bridge Modal Identification through an Inverse Problem Solution Procedure and Moving-Window Time Series Models.

With the rise and development of smart infrastructures, there has been a great demand for installing automatic monitoring systems on bridges, which are key members of transportation networks. In this regard, utilizing the data collected by the sensors mounted on the vehicles passing over the bridge can reduce the costs of the monitoring systems, compared with the traditional systems where fixed sensors are mounted on the bridge. This paper presents an innovative framework for determining the response and for identifying modal characteristics of the bridge, utilizing only the accelerometer sensors on the moving vehicle passing over it. In the proposed approach, the acceleration and displacement response of some virtual fixed nodes on the bridge is first determined using the acceleration response of the vehicle axles as the input. An inverse problem solution approach based on a linear and a novel cubic spline shape function provides the preliminary estimations of the bridge's displacement and acceleration responses, respectively. Since the inverse solution approach is only capable of determining the response signal of the nodes with high accuracy in the vicinity of the vehicle axles, a new moving-window signal prediction method based on auto-regressive with exogenous time series models (ARX) is proposed to complete the responses in the regions with large errors (invalid regions). The mode shapes and natural frequencies of the bridge are identified using a novel approach that integrates the results of singular value decomposition (SVD) on the predicted displacement responses and frequency domain decomposition (FDD) on the predicted acceleration responses. To evaluate the proposed framework, various numerical but realistic models for a single-span bridge under the effect of a moving mass are considered; the effects of different levels of ambient noise, the number of axles of the passing vehicle, and the effect of its speed on the accuracy of the method are investigated. The results show that the proposed method can identify the characteristics of the three main modes of the bridge with high accuracy.

Vocal count responses of narwhals to bulk carrier noise in Milne Inlet, Nunavut, Canada

AbstractConcerns were raised about possible behavioral disturbance to narwhals (Monodon monoceros) when exposed to shipping noise in Milne Inlet, Baffin Island, Canada. We deployed passive acoustic recorders in August and September 2018 and 2019, along and adjacent to the nominal shipping corridor. We measured broadband (0.01–25 kHz) sound pressure levels (SPL) after correcting for the auditory weighting function of high frequency cetaceans. Received SPLs and counts of Whistles, Buzzes, and Knocks were compared in a before‐during‐after study of individual bulk carrier transits, relative to periods with no ships. Narwhal call counts were generally lower once bulk carriers were within line‐of‐sight, including when ship noise levels were just above ambient noise levels. Call counts varied both “before” and “after” individual bulk carriers passed by the recorders. There was no evidence of a behavioral threshold SPL below which a response did not occur. We did not observe call count reductions to the same extent in 2019 compared to 2018 as higher ambient noise levels in 2019 likely masked some individual ship noise. There was no evidence of habituation or sensitization to the bulk carrier noise within or between years. Continued acoustic monitoring is recommended, especially if bulk carrier transits increase.

Ocean ambient noise on the Chukchi Plateau and its environmental correlates

Conducting research on ocean ambient noise under different sea ice conditions is highly important for the comprehension of the rapidly changing Arctic. We present the first results of ambient noise and its relationship to environmental forcing during the open-water, ice transition and ice-covered periods on the Chukchi Plateau. The ambient noise level (ANL) in the 20 Hz to 2 kHz band is higher, intermediate and lower during the open-water, ice transition and ice-covered periods, respectively. During the ice-covered period, the ambient noise is dominated by the ice-generated noise due to sea ice activities and shows a negative correlation with temperature. Therefore, when the temperature decreases, the sea ice is prone to shrinking and cracking, thus increasing the sea ice activities and resulting in increased ice-generated noise; when the temperature rises and is relatively high in May and June, the ANL is lowest for the sea ice inhibition to wind waves and decreased sea ice activities induced by temperature rise. Sea ice is the most predominant environmental factor affecting Arctic ocean ambient noise, and the ANL can potentially increase due to a reduction in Arctic sea ice and increase in human activities caused by global climate change.