bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of ripple width on ripple density resolution
Authors: Supin Alexander , Milekhina Olga N. , Nechaev Dmitry I. , Tomozova Marina
Published: May 2022

Effects of ripple width in rippled-spectrum signals on ripple density resolution was investigated. Two measurement paradigms were tested: (i) ripple density resolution for discrimination between two rippled signals and (ii) discrimination between a rippled test signal and non-rippled reference signal. The ripple widths varied from 9% to 64% of the ripple frequency spacing. For both paradigms, the ripple density resolution increased with deceasing the ripple width. For discrimination between two rippled signals, the resolution was 8.1 ripples/oct for a ripple width of 64% and increased to 15.1 ripples/oct at the ripple width of 9%. For discrimination between a rippled test and non-rippled reference signal, the resolution was 9.3 ripples/oct at a ripple width of 64% and increased to 85 ripples/oct at a ripple width of 9%. Discrimination between two rippled signals is hypothesized to depend on ripple depth in the excitation pattern; the depth increases with narrowing the ripple width. Discrimination between a rippled test and non-rippled reference signal is hypothesized to depend on temporal processing; the effect of the ripple width appears due to increasing the ratio of the autocorrelated to uncorrelated components of the input signal with narrowing the ripples.
Adaptation effects along a voice/non-voice continuum
Authors: Gao Zi , Oxenham Andrew J.
Published: May 2022

Adaptation, the selective decrease in neural responses following repeated stimulation, is likely important for perception in the face of variable sensory input. Previous researchers have observed contrastive adaptation effects involving speaker identity, gender, and vowels. The present study investigated whether such contrast effects can occur between voice and non-voice stimuli. A 10-step continuum between “voice” (/a/, /o/, or /u/ vowels) and “instrument” (bassoon, horn, or viola) was generated for each possible pair. In each trial, an adaptor, either voice or instrument, was played four times, followed by a test stimulus from along the appropriate continuum. When trials with voice and instrumental adaptors were grouped into separate blocks, strong contrastive adaptation effects were observed, with the test stimuli more likely to be identified as voice following instrumental adaptors and vice versa. Preliminary results comparing interleaved with blocked conditions and same-ear with different-ear conditions suggest longer-term build-up and persistence effects that may extend across both ears. [Work supported by NIH grant R01 DC012262.]
The impact of temporally coherent visual and vibrotactile cues on speech perception in noise performance
Authors: Oh Yonghee , Kalpin Nicole , Hunter Jessica
Published: May 2022

The inputs delivered to different sensory organs provide us with complementary information about the environment. Our recent study demonstrated that presenting abstract visual information of speech envelopes substantially improves speech perception ability in normal-hearing (NH), listeners [Yuan et al., J. Acoust. Soc. Am. (2020)]. The purpose of this study was to expand this audiovisual speech perception to the tactile domain. Twenty adults participated in sentence recognition threshold measurements in four different sensory modalities (AO: auditory-only; AV: auditory-visual; AT: audio-tactile; and AVT: audio-visual-tactile). The target sentence [CRM speech corpus, Bolia et al., J. Acoust. Soc. Am. (2000)] level was fixed at 60 dBA, and the masker (speech-shaped noise) levels were adaptively varied to find masked thresholds. The amplitudes of both visual and vibrotactile stimuli were temporally synchronized and non-synchronized with the target speech envelope for comparison. Results show that temporally coherent multi-modal stimulation (AV, AT, and AVT) significantly improves speech perception ability when compared to audio-only (AO) stimulation. These multisensory speech perception benefits were reduced when the cross-modal temporal coherence characteristics were eliminated. These findings suggest that multisensory interactions are fundamentally important for speech perception ability in NH listeners. The outcome of this multisensory speech processing highly depends on temporal coherence characteristics between multi-modal sensory inputs.
Examining potential sources of variability in behavioral measures of cochlear gain and gain reduction in listeners with normal hearing or minimal cochlear hearing loss
Authors: Strickland Elizabeth A. , Hopkins Anna , Rayner Andrea , Salloom William B. , Skaggs Miranda , Mielnicki Nicole , Morris Hayley , Holt Alexis
Published: May 2022

This study examined the relationship between clinical measures of auditory function and psychoacoustic measures related to cochlear function. Listeners’ audiometric thresholds for long tones ranged from well within the clinically normal range to just above this range. Where thresholds were elevated, other clinical tests were consistent with a cochlear origin. Because the medial olivocochlear reflex decreases cochlear gain in response to sound, measures were made with short stimuli. Signal frequencies were from 1 to 8 kHz. One point on the lower leg of the input/output function was measured by finding threshold masker level for a masker almost one octave below the signal frequency needed to mask a signal at 5 dB SL. Gain reduction was estimated by presenting a pink broadband noise precursor before the signal and masker and measuring the change in signal threshold as a function of precursor level. In a previous presentation, it was shown that the estimate of gain reduction decreased as quiet threshold increased, but was not solely determined by the amount of gain. In this presentation, the relationship between gain reduction and clinical otoacoustic emission and middle-ear muscle reflex measurements was examined to determine whether these explained some of the variability. [Work supported by NIH (NIDCD) R01 DC008327 (EAS) and NIH(NIDCD) T32 DC016853 (WBS).]
Discrimination of spectrotemporal ripple sweep direction near detection threshold
Authors: Conroy Christopher , Byrne Andrew J. , Kidd Gerald
Published: May 2022

There are single neurons in the auditory systems of some nonhuman animals that are sensitive to spectrotemporal ripples sweeping in one direction versus the other. We used a “2 × 2 forced-choice” simultaneous detection/discrimination paradigm [Nachmias and Weber, Vision Res. 15 217–223 (1975)] to search for behavioral evidence of similar neurons in the human auditory system (i.e., “labeled lines” for discriminating spectrotemporal ripple sweep direction). On each two-interval trial, observers were presented two successive sounds (one in each interval). One sound was an unmodulated noise and the other sound was a noise modulated by an upward-sweeping or downward-sweeping spectrotemporal ripple (±8 Hz/1 cycle/octave). Subsequently, observers registered two separate responses: a detection response (Which interval contained the ripple?) and a discrimination response (Was the ripple sweeping upward or downward?). Psychometric functions (proportion correct versus ripple-modulation depth) were constructed and compared for the two response categories. Labeled line theory predicts that the two functions should be identical: a correct detection response should always yield a correct discrimination response. Contrary to this prediction, observers required greater modulation depths to support discrimination than detection. This finding suggests that the detection of spectrotemporal ripples and the discrimination of spectrotemporal ripple sweep direction may depend on different mechanisms.
Predicting reflection patterns from binaural activity maps using deep neural networks
Authors: Tyler Jeramey , Si Mei , Braasch Jonas
Published: May 2022

A new model architecture is presented to predict room acoustical parameters from a running binaural signal. For this purpose, a deep neural network architecture is combined with a precedence effect model to extract the spatial and temporal locations of the direct signal and early reflections. The precedence effect model builds on the modified BICAM algorithm [Braasch, J. Acoust. Soc. Am. 140, EL143], for which the 1st layer auto-/cross correlation functions are replaced with a Cepstrum method. The latter allows a better separation of features relating to the source signal's early reflections and harmonic structure. The precedence effect model is used to create binaural activity maps that are analyzed by the neural network for pattern recognition. Anechoic orchestral recordings were reverberated by adding four early reflections and late reverberation to test the model. Head-related transfer functions were used to spatialize direct sound and early reflections. The model can identify the main reflection characteristics of a room, offering applications in numerous fields, including room acoustical assessment, acoustical analysis for virtual-reality applications, and modeling of human perception. [Work supported by the National Science Foundation under Grant No. IIS-1909229.]
Accurately targeting an arbitrary probability of response in staircase procedures
Authors: Hoover Eric C.
Published: May 2022

Staircase procedures are commonly used to identify the stimulus level corresponding to a specific probability of response. The primary benefit of staircase procedures is that they require only that the probability of response changes monotonically with the stimulus level. The probability of response targeted by the procedure is typically estimated from the mean of reversals. However, the mean of reversals can be asymptotically biased away from the targeted probability. Existing methods to address the bias add assumptions about task performance, thereby limiting their use to well understood tasks and listener groups. We evaluated the hypothesis that the bias could be mitigated without adding assumptions by accounting for the effect of invariant procedural parameters on the estimate of the target probability. The approach was successful for staircases with different ascending and descending steps, for which the bias was found to depend on step size only. For other staircases, predicting bias required adding assumptions comparable to existing solutions. Results suggest that the bias is caused by the factthat reversals are influenced by parameters that do not affect the target point. A method is proposed to accurately estimate an arbitrary probability of response without adding assumptions about the task or listeners. [R01DC015051.]
Effect of stimulus complexity on psychometric functions
Authors: Srinivasan Nirmal Kumar , Kansangra Radhika , Trotman Angelica
Published: May 2022

Factors such as semantic and syntactic context, predictability, talker characteristics, background noise characteristics, and spatial differences between the target and maskers play major role in identifying speech in complex listening environments. Here, we present psychometric properties of two closed set speech corpus: (1) co-ordinate response measure (CRM) and (2) Boston University Corpus (BUC) obtained from a group of fifty young normal-hearing, listeners. CRM sentences are of the form “Ready CALLSIGN go to a COLOR NUMBER now” and BUC sentences are of the form “NAME VERB NUMBER ADJECTIVE NOUN.” Method of constant stimuli was used to obtain psychometric functions for the two corpora in the presence of speech and speech shaped noise. One half of the participants were presented the stimuli at a constant level (20 dB SL), while it was presented at comfortable listening levels for the half. The effect of the stimulus complexity, presentation level, and spatial configuration of the target and noise on the identification thresholds and the shape of the psychometric functions will be discussed.
Aerogel-based ultralight noise absorbers fabricated using 3D freeze printing
Authors: Yang Guang , Sharma Bhisham , Lin Dong , Lei Shuting
Published: May 2022

Aerogels are a group of synthetic materials with a structure comprising up to 99.8% air. This ultra-sparse skeletal structure results in extremely low-density and thermal conductivity. Because of these extreme properties, aerogels are highly attractive for thermal insulation and energy absorption applications. In acoustics, their application is typically limited to their use as granular material—either as granular layers or as additives to conventional fibrous and matrix materials. Here, we explore the possibility of controlling not only their mesostructure but also their macrostructure by fabricating aerogel-based ultralight noise absorbers using a 3-D Freeze Printing (3DFP) technique. First, we introduce the novel 3DFP method, which combines the advantages of additive manufacturing and freeze casting processes. Next, we focus on the acoustic characterization of 3-D freeze printed aerogels using a normal incidence impedance tube setup. Our results show that compared with current passive noise reduction materials, the unique structures generated by the 3DFP method can provide significantly improved absorption and transmission loss properties.
Sound absorption properties of spinodoid structures with spatially varying properties
Authors: Sharma Bhisham , Wojciechowski Brittany
Published: May 2022

Creating lightweight structures with tailored noise reduction at low-frequencies remains a major engineering challenge. Open-celled porous structures with low relative densities offer a possible solution to this problem. Spinodoids—structures with microstructural architectures based on spinodal decomposition—have been recently shown to provide robust and tunable mechanical properties. Here, we study the sound absorption properties of spinodoids with spatially varying properties such as relative density, spinodoid type, and wavenumbers. We generate the sample geometries using MATLAB and print them using low-cost additive manufacturing methods. The printed samples were then tested using a normal impedance tube setup to characterize their absorption coefficients. Our results show that spatially gradient spinodoids provide an attractive solution for designing multifunctional structures with application-specific acoustic properties.
Vibration response and acoustic radiation of a thin floating plate
Authors: King Allison M. , Dowling David R.
Published: May 2022

Remote sensing may be used to detect and locate acoustic sources on a thin floating plate as well as predict the geometry and material of the structure based on recordings of vibratory and acoustic waves. Remote detection and localization of impacts on a thin floating structure is desirable. For a transient excited thin floating structure, the coupling of the vibration waves in the structure and the acoustic waves radiating from it into the air above and water below can introduce complexity not encountered with traditional source identification techniques. To study this problem, repeatable axisymmetric transient impact experiments are conducted in a 1.2-m diameter cylindrical water tank by dropping a stainless-steel ball bearing onto a 6.4-mm-thick aluminum plate suspended at the air-water interface. Accelerometers and laser Doppler vibrometry are used to record the vibration of the plate. Acoustic radiation is recorded in the air above the plate and in the water below it using linear arrays of 6 microphones and hydrophones, respectively. Wave speeds in the plate ranging between 430 m/s and 1550 m/s are considered. Results are compared to a combined acoustic-structure finite element model. [Sponsored by NAVSEA through the NEEC.]
Experimentally determining power flow in cylindrical shells using a scanning laser Doppler vibrometer
Authors: Ruchti Tysum , Blotter Jonathan D. , Sommerfeldt Scott D.
Published: May 2022

Power flow methods are used to identify energy sources and sinks in objects and to visualize transmission pathways. The most common method uses surface acceleration or velocity measurements and finite difference methods to compute power flow. In flat structures, a scanning laser Doppler vibrometer (SLDV) has been used to increase the measurement resolution. For more complicated surfaces, the general approach has been to use accelerometers at a few key points and measure transmission rather than seeking to get a full visualization of the power flow. This research uses a 3-D-SLDV to take surface velocity measurements for a simply supported cylinder. The 3-D velocity data is used to solve for a quintic B-spline representation of the velocity field. Similar representations for each of the force resultants are generated using an isotropic material model and the Love equations for cylindrical shells. The resultant and velocity fields are used to compute the direction and magnitude of the energy transfer. This method is validated by comparing experimental results to the outputs of an analytical solution and to a finite element model.
Improved efficiency of vibration-based sound power computation through multi-layered radiation resistance matrix symmetry
Authors: Ebeling John C. , Bacon Ian C. , Bates Trent P. , Sommerfeldt Scott D. , Blotter Jonathan D.
Published: May 2022

Calculating sound power using complex-valued surface velocities is becoming an established practice in structural acoustics with rising optimism about this method’s potential versatility compared to traditional pressure-based methods. One approach involves using a geometry-dependent acoustic radiation resistance matrix multiplied by a velocity vector to compute sound power for a given frequency range. At scale, the computational costs incurred through this calculation limits the application of this method. Given a discretized surface with constant spacing and using a well-informed average radiator area approximation, a multilayered Toeplitz symmetry exists in the radiation resistance matrix. This symmetry, its origins and necessary assumptions are explored. By exploiting the Toeplitz symmetry, computationally expensive mathematical operations that used to be performed on the entire radiation resistance matrix, can be performed on a single row of the matrix, and then expanded using the pattern that will be presented. This approach preserves accuracy and greatly accelerates the processing, as evidenced through experimental data. The approach resulted in a maximum of ∼1300% computation time reduction for single radius curved plate calculations and a ∼9,600% computation time reduction for cylindrical shell calculations. [Funding for this work was provided by the National Science Foundation (NSF).]
V-to-V coarticulation may be extinct in the wild
Authors: Scott Hannah J. , Fulop Sean A.
Published: May 2022

Ever since the results of [S. E. G. Öhman, “Coarticulation…,” J. Ascoust. Soc. Am. 39, 151 (1966)] that a vowel could affect the preceding one, the phenomenon of anticipatory VCV coarticulation has been a subject of study. Most results establishing these effects have been obtained from curated laboratory speech [e.g., M. Grosvald, “Interspeaker variation…,” J. Phonetics 37, 173 (2009)], showing anticipatory V-to-V coarticulation across one, two and three syllables in English utterances. Here, we attempted to replicate these findings “in the wild” using the Buckeye Corpus of conversational English. F1 and F2 of [ʌ] or [ə] tokens were obtained in all [ʌ/ə]C(C…)V contexts. Two-dimensional Kolmogorov-Smirnoff tests were carried out to compare the F1/F2 distributions of these tokens in different contexts. The formant distributions of [ʌ/ə] in specific vowel contexts were also compared with the total formant distributions of [ʌ/ə] in all contexts. The replication effort was a failure. Essentially no significant differences of the [ʌ/ə] formant distributions could be found among the data, no matter how extreme the difference of the following vowel (e.g., [i] vs [ɑ] contexts). This poses a problem for theories of speech perception which rely on such effects.
Prediction model formulations for detection, enumeration, and localization of multiple sound sources using spherical harmonics
Authors: Xiang Ning , Metzger Thomas
Published: May 2022

A spherical microphone array is used to detect and localize sound sources in terms of model-based machine learning (ML). In this application, it is crucial to establish parametric models to distinguish background sound environment from presence of sound sources. In the presence of sound sources, the parameter models are also used to localize an unknown number of potentially multiple sound sources. In this work, a model-based Bayesian learning framework is presented for localizing an unknown number of sound sources. Among them, a no-source scenario needs to be accounted for. The model-based machine learning applies the model comparison between the no-source model and the one-source model for sound source detection. After detecting sound sources, the machine learning needs to involve sound source enumeration and localization in order to correctly localize potential multiple sound sources. Specifically, sound environment is analyzed using Bayesian model comparison of two different models accounting for absence and presence of the sound sources for source detection. Upon a positive detection, potentially multiple source models are involved to analyze direction of arrivals (DoAs) for far-field and to localize sound sources for near-field including source distances, amplitudes, and DoAs using Bayesian model selection and parameter estimation.
Ice anthropogenic classification with acoustic vector sensors using transformer neural networks
Authors: Whitaker Steven , Barnard Andrew , Anderson George D. , Havens Timothy
Published: May 2022

Acoustic classifiers are a necessary component in understanding the source. When a foreign object has been classified, physics models can be associated with the foreign object for better localization and tracking. In highly non-linear environments, like shallow ice environments, traditional classifiers cannot properly consider its compounded non-linearities: multi-path, reflective surfaces, scattering fields, and the dynamic acoustic properties of first-year ice. With such significantly distorted signals, we deploy deep neural networks to better classify different acoustic sources. We collected data from 8 different acoustic sources on the Keweenaw Waterway in Houghton, Michigan: a narrow and shallow channel covered with first-year ice. Two sources were moving and the other five were stationary; the sources did not emit simultaneously. Data were recorded using two spatially separated underwater acoustic vector sensors; their time-series data were post-processed into mel-frequency cepstral coefficients (MFCC) and analyzed with different deep neural network architectures. A deep Transformer neural network and a deep residual neural network were then compared in their ability to predict which source was emitting. Preliminary results show success with the deep Transformer neural networks.
Resolution of matched field processing for a single hydrophone in a rigid waveguide
Authors: Cheney Margaret , Kirsteins Ivars
Published: May 2022

This paper studies resolution of matched field processing for locating, in range and depth, a broadband underwater acoustic source from data measured at a single hydrophone receiver. For the case of an ideal rigid shallow-water waveguide with a pressure-release top boundary and a rigid bottom boundary, we derive approximations for the main-lobe widths of the ambiguity surface. The two cases studied in this paper are (1) when coherent measurements of the pressure are available, with the transmitted source waveform precisely known, and (2) when only measurements of the received signal power spectral density (PSD) are available, such as occur when the transmitted signal is random and unknown. The analysis uses the normal-mode expansion for the pressure field to derive approximate expressions for the ambiguity surface main-lobe widths, as a function of the number of modes and frequency band, for both range and depth. Numerical results are presented corroborating the analytical analysis. Finally, we argue that this ambiguity analysis also gives insights into real ocean waveguide localization characteristics under appropriate conditions, and show numerical simulations of matched field localization ambiguity surfaces for some realistic shallow-water Pekeris environments.
Sensitivity of spatial coherence of sub-bottom scattering to sediment attenuation
Authors: Matriss Anthony P. , Brown Daniel C. , Blanford Thomas E.
Published: May 2022

The spatial coherence of seafloor scattering is determined by a complex interaction between parameters describing the environment, the sensor, and the measurement geometry. Forward modeling shows that near normal incidence, the spatial coherence of the field backscattered from an isotropic sub-bottom may be sensitive to the sediment attenuation coefficient. This presentation will describe a parametric study investigating the sensitivity of spatial coherence to specific combinations of environment, sensor, and measurement geometry. Particular emphasis will be placed on identifying configurations where the spatial coherence is sensitive to the sediment attenuation coefficient. To support this analysis, a numerical model using the van Cittert–Zernike Theorem and a point-based scattering model will be used to provide forward modeling of the spatial coherence. These models are compared for several simulated environments of increasing complexity to explore the sensitivity of the spatial coherence to sediment attenuation. Agreement between these models will provide a path to developing the collection geometry and algorithms necessary for inversion using simulated data.
Centralized data repositories: NOAA’s National Archives for Marine Acoustic Data
Authors: Martinez Veronica , Anderson Charles , Wall Carrie , Jimenez Elizabeth
Published: May 2022

The NOAA National Centers for Environmental Information maintains two marine acoustic archives for the long-term stewardship of globally collected water-column sonar and passive acoustic data. These vast datasets are collected across NOAA and academia for a wide range of scientific objectives. The archives document the datasets using standards-driven metadata and preserve them on long-term storage systems. Users can discover, query, and access archived data using the archives’ web-based map viewers. Further, cloud-based access to 200 + TB through the NOAA Big Data Program enables free and immediate download of desired data and allows users to bring processing routines to large volumes of data—from simple statistical analyses to artificial intelligence. Cloud-based tools are being developed in collaboration with our partners in the ocean acoustic community to visualize and analyze data in the archives. This allows researchers of varying backgrounds to easily understand the quality and content of these complex data. Providing free access to data archives and facilitating the utility of these data increases the potential for researchers to address new questions that will advance the field of marine ecosystem acoustics.
Modifying a recital hall to extend its range of use: A case study
Authors: Sacks Jonah , Markham Benjamin E.
Published: May 2022

Rosen Concert Hall, in the Broyhill Music Center at the Appalachian State University Hayes School of Music, is a beloved 400-seat recital hall designed in the 1980s by architect Dennis Yates and acoustician Rein Pirn (Acentech/BBN) and was featured in the 1990 ASA publication “Acoustical Design of Music Education Facilities.” The hall was designed for pipe organ, vocal chorus, and smaller classical instrumental ensembles, with significant variable absorption in the form of curtains. Since then, the school’s program has broadened, and the hall is now used also for jazz band, large wind ensemble, and some amplified forms. A 2017 study included acoustical measurements in the hall, listening sessions with eight different ensembles in the hall, and discussions with faculty and staff. These resulted in detailed recommendations for acoustical improvements and new audiovisual equipment. The school has completed two recommended acoustical improvements, with positive results: hinged absorptive wall panels surrounding the platform, and extended reflective canopy. Users report improved on-platform clarity for louder ensembles, and better self-hearing and presence of sound for downstage performance locations.
Auralization of a flexible recital hall
Authors: Avendano-Gutierrez Efrain , Rogers Kelsey , Markham Benjamin E.
Published: May 2022

Auralizations have proven to be a powerful tool when it comes to the design phase of a room. They allow consultants to analyze and convey the acoustical challenges to make decisions accordingly. For this presentation, we look at the process of creating auralizations for a multipurpose recital hall, and how the different configurations of the room affect it acoustically. The recital hall will need to accommodate a large variety of rehearsals and performances, ranging from solo musicians to large combined ensembles. Therefore the balance between stage, audience, and ensemble must be kept in mind, spatially and acoustically. This project and presentation is thanks to the SURIEA program; an intensive summer program that emphasizes training, mentoring, research, and preparing students for graduate studies and careers in acoustics. As part of the program, students were paired with mentors to work on a project, and present their results in the next ASA conference.
Operational underwater sound from future offshore wind turbines can affect the behavior of marine mammals
Authors: Thomsen Frank , Stöber Uwe
Published: May 2022

Offshore wind farms are part of the transition to renewable sources of energy and both the total numbers and size of wind turbines are rapidly increasing. While the impact of underwater sound related to construction work has been in the focus of research and regulation, few data exist on the potential impact of underwater sound from operational wind farms. Here, we reviewed published sound levels of underwater sound from operational wind farms and found an increase with size of wind turbines expressed in terms of their nominal power. This trend was identified in both broadband and turbine-specific spectral band sound pressure levels (SPLs). For a nominal power of 10 MW, the trends in broadband SPLs and turbine-specific spectral band SPLs yielded source levels of 170 and 177 dB re 1 μPa m, respectively. The shift from using gear boxes to direct drive technology is expected to reduce the sound level by 10 dB. Using the U.S. regulatory criterion for behavioral disruption for continuous noise (i.e., level B), a single 10MW direct drive turbine is expected to cause behavioral response in marine mammals up to 1.4 km distance from the turbine, compared to 6.3 km for a turbine with gear box.
Quantifying ship noise bias in fish abundance estimates in the Great Lakes
Authors: Barnard Andrew , Penhale Miles , Senczyszyn Steven , Kocher Erik , Swain Jason , Esselman Peter
Published: May 2022

Prey fish abundances in the Great Lakes are a driver for several agencies commitments to the Council of Lake Committees to support fisheries management. These management decisions have profound economic and social impacts within the Great Lakes region. Fisheries estimates done by echosounders or trawling may be biased due to the propagated noise from large fisheries vessels. In the first year of a four year collaborative study, crewed fisheries vessels and uncrewed Saildrone vessels were used to compare abundance estimates between “loud” and “quiet” vessels. In order to quantify the effects of ship noise on prey fish abundance estimates, a mobile ship noise measurement system was designed and deployed to measure radiated acoustic signatures of several ships in the Great Lakes. This talk will discuss the deployment of a mobile underwater acoustic test range, and show initial results of ship noise measurements from the first year of the program. In addition, an overview of the echosounder abundance results will be given along with plans for future data generation, analysis, and comparison between crewed and autonomous systems.
Spatio-temporal contrastive learning for acoustic data
Authors: Zhang Yawen , Wall Carrie , Jech J Michael , Lv Qin
Published: May 2022

Large volumes of water column sonar data have been generated from acoustic surveys of living marine resources. They provide valuable information about marine ecosystems. To leverage them for acoustic target identification, scarcity of annotations is usually an issue. While some annotations have been generated by scientists via manual scrutiny or limited automation, they are limited to certain species. To fill in this gap, we propose a spatio-temporal contrastive learning approach for acoustic data. This unsupervised deep learning technique leverages both acoustic and non-acoustic (spatial and temporal) information for acoustic target classification. We firstly employ the Simple Linear Iterative Clustering (SLIC) algorithm to extract superpixels from acoustic data. Then the spatial and temporal similarity between two superpixels is computed, and the proposed spatio-temporal contrastive learning approach is applied to learn a semantically meaningful representation for superpixels. Finally, the learned representations of superpixels are used in acoustic target classification. We demonstrate that this approach outperforms previous methods with acoustic data collected by the NOAA National Marine Fisheries Service in the Gulf of Maine and Georges Bank region over 10 years. This dataset is archived at NOAA National Centers for Environmental Information and accessed for free through AWS and NOAA Big Data Program.
The effects of array design on acoustic data collected during marine seismic reflection surveys
Authors: Douglass Alexander S. , Wood Warren T. , Phrampus Benjamin J. , Abadi Shima
Published: May 2022

Marine seismic reflection surveys provide an abundance of acoustic data that are potentially useful for an array of analyses within and in addition to geoacoustic studies. A single cruise typically produces thousands to tens of thousands of acoustic events, with hundreds of hydrophones recording each event over towed arrays that can span up to 15 km or more. However, the structure of the airgun source arrays and the receiver arrays is typically not obvious from the data alone and the pre-processing of the data may yield misleading results if not properly accounted for. Generally, the acoustic source consists of an array of airguns configured such that the acoustic energy is focused towards the ocean floor, significantly impacting the relative intensity of the direct and reflected paths. Additionally, each array channel output typically consists of multiple hydrophone outputs, which are not individually available, averaged to generate a single channel output. Understanding the impact of these constructions is crucial for many analyses, such as mitigation of airgun pulse impacts on marine mammals. Here, we quantify the impact that these factors have on the output data and provide an analysis of this influence for an experimental case. [Work supported by ONR.]
Modal dispersion curve extraction from shipping noise at two synchronized vertical arrays
Authors: Yarina Marina , Lun'kov Andrey , Godin Oleg A. , Katsnelson Boris
Published: May 2022

The results of modal dispersion analysis, using low-frequency (20 to 250 Hz) shipping noise in shallow water with a soft bottom is presented. Experiments were carried out in the Sea of Galilee (Lake Kinneret, Israel) having a maximum depth of ∼40 m and a gassy upper sedimentary layer. A receiving system combined two synchronized, 10-hydrophone vertical line arrays (VLAs) located at the center of the lake with distance Dr = 40 m between them. The noise source, R/V “Hermona,” was moving along the straight line joining VLAs, up to 1 km from VLAs. A method of obtaining modal dispersion curves from shipping noise is proposed. For each frequency ω and variable horizontal wavenumber q = ω/cph the noise is spatially filtered at each VLA using calculated solution of the wave equation with the measured sound speed profile in water and the pressure-release condition imposed at the water surface. Then, the ratio of complex modal amplitudes at VLAs is calculated and multiplied by a factor of . The real part of the resulting 2-D structure exhibits the modal dispersion curves, which are used for acoustic characterization of the seabed. [Work supported by ISF, grant 946/20, and RFBR, grant 20-05-00119.]
High data rate ultrasonic communications
Authors: Singer Andrew C. , Tabak Gizem , Oelze Michael L.
Published: May 2022

Ultrasonic signals have been used in biomedical applications since at least the 1940s. Underwater acoustic signals have been used in the subsea industry for ranging since the early 1900s and for SONAR imaging and communication in the decades that followed. Since the development of subsea communication systems in the 1940s, increasingly sophisticated means have be developed for transmitting information acoustically through the highly variable ocean environment. State-of-the-art acoustic communication systems leverage ultrasonic transducers to achieve data transmission rates that mirror radio-frequency (RF)-based WiFi systems on land. The increasing use of wireless implanted medical devices (IMDs) have increased interest in through-tissue communications. Restrictions on the available bandwidth and transmit signal power limit the data rates of RF-based IMDs. In this talk, we give an overview of video-capable ultrasonic wireless communication between IMDs and external devices. We emphasize the potential of such a system for improving video capsule endoscopy and describe the challenges of through-tissue acoustic communication. Building on experience with subsea-communication systems, we discuss methods to cope with attenuation, dispersion, reflection, and nonlinear propagation. Some of our recent experiments performed ex vivo with soft tissue samples and in vivo with anesthetized animal subjects will be discussed.
Measurements of electromechanical impedance to determine effects of pressure and temperature on underwater acoustic transducers
Authors: Aikins Eric K. , Brown David A.
Published: May 2022

Underwater electroacoustic transducers can be subjected to large static pressures, wide range of temperature, and high operational electric fields causing internal heating. These conditions can adversely impact the performance of transducers including transmit output source level, reliability, survivability, useable bandwidth, tuning and matching to the amplifier, and efficiency. A low cost electroacoustic impedance measurement system was implemented with an air-pressurized mechanical transformer using SCUBA tanks to investigate transducer properties to 1,500 PSI. Subsequently, a water pressurized tank was used to 10 000 psi (or 7000 m of equivalent depth). A variety of underwater cylindrical transducers were tested and the changes in electromechanical properties (dielectric constant, capacitance, loss-tangent, mechanical compliance, piezoelectric d-constant, and effective coupling constant) were measured dynamically using the impedance methods. An analytical model was developed with a GUI to predict acoustic performance and tuning for different operational (depth, temperature, and drive level) conditions. Cylindrical transducers of oil-filled and polyurethane filled designs were shown to have moderate changes in electromechanical properties to pressures of 10 000 psi.
Quasi-anechoic frequency response measurement of underwater acoustic devices using exponential sine sweeps
Authors: Dominijanni Andrew , Rowan Jeffrey
Published: May 2022

As part of the development of the MITRE BlueTech Lab, an existing 106 × 40 × 15 ft. underground tank is being repurposed as an underwater acoustic test facility. Here, we report on the development of a procedure to extract anechoic frequency responses from measurements made in the otherwise reverberant environment using exponential sine sweeps. A demonstration of the procedure applied to a small-aperture baffled receiver array is shown, and results are compared to time-gated stepped sine wave measurements. Simple geometric rules to maximize measurement bandwidth while ensuring far-field conditions for both transmitter and receiver array are presented.
Design of acoustic metasurfaces with independent phase and amplitude control
Authors: Krishna Arvind , Craig Steven R. , Shi Chengzhi , Joseph Roshan V.
Published: May 2022

We address the problem of designing acoustic metasurfaces for independent amplitude and phase control of acoustic waves. The reflection and transmission amplitude and phase of an acoustic wave are governed by the geometry of the acoustic metasurface. The geometry is modeled by discretizing the continuous space into a finite number of elements, where each element can either be filled with air, or solid material. Full wave simulations on the COMSOL Multiphysics software are performed to obtain the acoustic outputs for a given geometry. In case of smaller-sized elements, it is computationally infeasible to consider all geometries, which correspond to all possible combinations of solid or air-filled elements. To address this challenge, we propose a novel ‘acoustic domain space expansion algorithm’ that starts with a few geometries and adaptively adds geometries to the set such that they span the entire domain of the desired acoustic outputs, using only a small fraction of all the possible geometries. Our algorithm simulated only 24 000 geometries out of the 563 trillion possible geometries, which can be used to obtain any feasible combination of the acoustic outputs with a tolerance of 5.4% in the individual outputs.
Acoustic metamaterial-based neural network for task solving
Authors: Weng Jingkai , Ding Yujing , Liang Bin , Zhu Xuefeng , Yang Jing , Cheng Jian-chun
Published: May 2022

Simple and precise sound manipulation is of fundamental interest and practical significance in acoustics and many related fields. The recent emergence of acoustic metamaterials offers acoustic properties unattainable in the nature and opens up possibility for controlling sound, which may also find applications in diverse scenarios. However, acoustic metamaterials still cannot directly solve complicated tasks, such as recognition of objects that needs to analyze scattered wave. Deep learning technique helps to eliminate the conventional dependence on human experts, but is still arouse issues of computation complexity, energy supply, device size and cost. We build a passive neural network by using numerous metamaterial unit cells, whose phase shifts are chosen as learnable parameters for the machine learning training. Such a metamaterial-based neural network interacts with the scattered wave produced by the object and accurately redistributes the output energy on a detection plane, exhibiting the “intelligence” to perform complex machine-learning tasks. Its equivalence with a conventional neural network is analytically proved, and its task-solving performance is numerically and experimentally demonstrated. More importantly, detection and computation are performed simultaneously, and the computational complexity or energy consumption will not increase even if the object becomes more complicated.
Efficient artificial intelligence techniques for inverse design and knowledge discovery in metamaterials
Authors: Zandehshahvar Mohammadreza , Kiarashinejad Yashar , Hadighe Javani Mohammad , Zhu Muliang , Brown Tyler , Bao Daqian , Adibi Ali
Published: May 2022

A new artificial-intelligence (AI) approach based on dimensionality reduction techniques for the design and knowledge discovery in metamaterial structures will be presented. It is shown that reducing the dimensionality of the response and design spaces by using a pseudoencoder can reduce the computation time by 2–3 orders of magnitude. In addition, using pruning techniques can simplify the trained algorithm to further reduce the computation time while providing simpler paths for relating input-output relationships for understanding the role of design parameters (i.e., knowledge discovery). It is also shown that this approach can enable an evolutionary design method in which the initial design can be evolved intelligently into an alternative with favorable specifications. The application of these AI approaches for both optical and acoustic metamaterials will be presented.
Sound localization via deep learning, generative modeling, and global optimization
Authors: Wang Wei-Ching
Published: May 2022

An acoustic lens is capable of focusing incident plane waves at the focal point. This talk will discuss a new approach to design metamaterials with a focusing effect using effective and innovative methods by using machine learning. Specifically, the physics simulations use multiple scattering theory and machine learning techniques such as deep learning and generative modeling. The 2-D-Global Optimization Networks (2-D-GLOnets) model [1] developed initially for acoustic cloak design is adapted and generalized to design and optimize the acoustic lens. We supply the absolute pressure amplitude and gradient into the deep learning algorithms to discover the optimal scatterer positions that maximize the absolute pressure at the focal point in the confined region. We examine and evaluate the performance of the generative network, searching for an optimal configuration of scatterers over a range of parameters to produce desired features, such as broadband focusing and localization effects. The model will show examples of planar configurations of cylindrical structures producing focusing effect. [1] L. Zhuo and F. Amirkulova, “Design of acoustic cloak using generative modeling and gradient-based optimization,” in INTER-NOISE and NOISE-CON Congress and Conference Proceedings (Institute of Noise Control Engineering, 2021), Vol. 3.
Pentamode metamaterial design via generative modeling and deep learning
Authors: Qiu Cheng , Abbas Anam , Amirkulova Feruza
Published: May 2022

In this talk, the deep learning-assisted models will be presented for the design of pentamode unit cells to construct a 3-D lattice structure that can mimic the acoustic properties of water. The pentamode models were implemented and modified by altering the properties of the structure during the full-wave simulation performed on COMSOL Multiphysics software to ensure they meet the requirements of specific appliances for manufacture. The design is further improved by the inverse design technique. The implementation of conditional Wasserstein Generative Adversarial Networks with gradient penalty (cWGAN-GP) for the inverse design will be illustrated by showing examples of 3-D titanium pentamode structures on the hexagonal lattice. The cWGAN was set up using critic and generator with CoordConv layers, along with regressor to produce images matching the desired labels. The convolutional neural network was used as an auxiliary regressor to predict all design parameters for the cell images. The expected PM lattice structure has a high bulk modulus, low-shear modulus and behaves as metal water at a broad range of frequencies including higher frequencies.