bluuebunny/crossref_metadata_2025 huggingface dataset:
Reconfigurable metamaterial neuromorphic computing
Authors: Moghaddaszadeh Mohammadreza , Mousa Mohamed , Aref Amjad , Nouh Mostafa
Published: November 2022

Neuromorphic computing was originally introduced in electronic circuits to mimic neuro-biological architectures. In these systems, a physical agent (e.g., an electromagnetic or acoustic wave) propagates through multiple layers of metasurfaces which are trained to perform a computational task (e.g., classification). Despite their potential, current neuromorphic metasurfaces rely on passive designs which limits their computational power to a single task. Furthermore, attempts to realize these systems in the context of mechanical wave propagation have been very scarce. This work presents a neuromorphic metasurface which is designed to exploit elastic wave scattering to realize a physical computing environment. Owing to the reconfigurable design of the chosen unit cell, the neuromorphic metasurface can be tuned to conduct multiple distinct classification tasks without the need for remanufacturing. The designed subwavelength metasurface cell will be used to train a customized neural network with constant weights (representing the elastic wave propagation between different layers of metasurface) and trainable activation functions (representing the phase modulation at each layer of metasurface). To perform distinct classification tasks, the trainable parameter in the activation function will be tuned accordingly. This work opens up new avenues in high performance mechanical computing.
Strongly tunable nonlinear MEMS resonators by electro-thermoelastic buckling
Authors: Kanj Ali , Ferrari Paolo F , van der Zande Arend M. , Vakakis Alexander F. , Tawfick Sameh
Published: November 2022

This talk presents the benefit of buckling in strongly tuning nonlinear MEMS resonators. In particular, the talk shows experimental buckling achieving more than 230% tuning in the natural frequency of drumhead MEMS resonators. Moreover, the experiments demonstrate that buckling switches the frequency response between purely stiffening, purely softening, and stiffening-to-softening nonlinearities. We tune the buckling state in these experiments by controlling the electric voltage and the temperature of the resonators. Therefore, these resonators undergo electrostatically-mediated thermoelastic buckling where specific combinations of temperature and voltage are required to access the distinct vibrational responses. We explain the observed linear and nonlinear responses by a reduced-order model (ROM) that lumps the resonator into a 1-degree-of-freedom mass connected to springs reflecting bending, stretching, electrostatic forces, thermal expansions, and residual stresses. The ROM mimics von Mises trusses to model the buckling in the membrane resonators without the need for exact geometry or structure to model the resonators. This developed ROM and the electro-thermoelastic buckling tunability present useful applications for on-chip acoustic devices in different fields such as signal manipulation, filtering, and MEMS waveguides.
Graph representation learning on braid manifolds
Authors: Christensen Andrew J. , Sen Gupta Ananya , Kirsteins Ivars
Published: November 2022

The accuracy of autonomous sonar target recognition systems is usually hindered by morphing target features, unknown target geometry, and uncertainty caused by waveguide distortions to signal. Common “black-box” neural networks are not effective in addressing these challenges since they do not produce physically interpretable features. This work seeks to use recent advancements in machine learning to extract braid features that can be interpreted by a domain expert. We utilize Graph Neural Networks (GNNs) to discover braid manifolds in sonar ping spectra data. This approach represents the sonar ping data as a sequence of timestamped, sparse, dynamic graphs. These dynamic graph sequences are used as input into a GNN to produce feature dictionaries. GNNs ability to learn on complex systems of interactions help make them resilient to environmental uncertainty. To learn the evolving braid-like features of the sonar ping spectra graphs, a modified variation of Temporal Graph Networks (TGNs) is used. TGNs can perform prediction and classification tasks on timestamped dynamic graphs. The modified TGN in this work models the evolution of the sonar ping spectra graph to eventually perform graph-based classification. [Work supported by ONR grant N00014-21-1-2420.]
Ultrasonic properties of human scalp
Authors: Labuda Cecille , Lawler Blake C. , Harbert Shona C. , Hoffmeister Brent K.
Published: November 2022

The goal of this study was to characterize the ultrasonic properties of human scalp. Thirty-two specimens were prepared from formalin-fixed scalp tissue from four human donors (age 35–65, 2 male, 2 female). Tissue specimens were mounted in acrylic frames with a 30 × 30-mm acoustic window. The specimens were scanned in a water tank with a broadband ultrasound transducer with center frequency 7.5 MHz using a motion-controlled system. The ultrasonic region of interest (ROI) was a 20 × 20-mm region with a step size of 410 μm. The signals acquired were analyzed to determine the speed of sound (SOS) and frequency slope of attenuation (FSA) at all scan locations (2500 locations per specimen). The mean ± standard deviation (SD) of the SOS and FSA over all the specimens respectively was 1536 ± 9 m/s and 1.88 ± 0.51 dBcm-1MHz-1. The SD within an ROI was 3–15 m/s for SOS and 0.15–0.85 dBcm-1MHz-1 for FSA, depending on specimen, indicating some heterogeneity in the ultrasonic properties of the tissue.
Learning both a value and uncertainty label for seabed parameters from ship noise data
Authors: Mortenson Michael C. , Neilsen Tracianne B. , Transtrum Mark K. , Knobles David P.
Published: November 2022

Because the seabed impacts sound propagation in the ocean, machine learning is being used for both seabed classification and to obtain estimates of individual seabed properties. This paper proposes a method to simultaneously estimate these properties and an associated uncertainty label. A residual neural network is trained and validated using synthetic ship noise spectrograms generated with a range-independent normal mode sound propagation model and a ship noise source spectrum. The data set includes 140 seabeds: In each, the top sediment layer has a random thickness and properties randomly chosen from five sets of bounds, which roughly correspond to clay, mud, sand, silt, and gravel. For each of the 140 sediments, a random selection of 405 combinations of ship speed, closest-point-of-approach range, and source depth are used resulting in 22k data samples. Each data sample is labeled with the true values of the sediment parameters as well as a label for the uncertainty level of each. The uncertainty levels are obtained from the Fisher information and qualify of the information content in the ship spectrogram about each parameter. Examples of how the residual neural network learns to perform regression for the parameter value and the uncertainty level will be presented.
Broadband multimode piezoelectric spherical shell transducers for underwater sound
Authors: Brown David A. , Souza Austin , Bachand Corey , Bisbano Michael
Published: November 2022

Broadband multimode piezoelectric spherical shell transducers are investigated for underwater sound by exciting the zeroth and/or first order (0 + 1) extensional modes of vibration with and without acoustical baffles of different types. Measurements of the frequency response (transmit pressure per volt or TVR), radiation patterns and electromechanical impedance reveal useful tradeoffs and design guidance for many practical applications. Measurements are in good agreement with theoretical closed form analytical results.
Mechatronic acoustic research system for generating real large-scale dynamic datasets
Authors: Lu Austin , Moore Ethaniel , Nallanthighall Arya , Sidhu Mankeerat S. , Sarkar Kanad , Mittal Manan , Corey Ryan M. , Smaragdis Paris , Singer Andrew C.
Published: November 2022

To support spatial audio research, we aim to take recordings from complex acoustic environments with moving sources and microphones, however we observe a lack of research tools that can accomplish this. Past approaches recorded people engaging in various tasks, which produces rich data that unfortunately lacks repeatability. We propose using robots to recreate dynamic scenes without the inherent variability of human motion. To be useful, this Mechatronic Acoustic Research System must be remotely accessible, offer concise representations of dynamic scenes, support a variety of robot and audio devices, and synchronize robot motion. In this talk, we show how we solved these challenges. Remote experimentation is facilitated by our virtual interface, which uses a simple GUI to describe robot motion and audio playback/recording. A digital twin physical simulation is used for visualization and validation of motion paths. We propose using the Robot Operating System for multi-robot coordination so that networked robots can be incorporated with little overhead. We use MARS to run experiments where a cable-driven parallel robot moves a loudspeaker along a 3D path while being recorded from distributed Matrix Voice microphone arrays. We evaluate the measured audio to show repeatability of the system, justifying its use in research.
The impact of formal musical training on speech intelligibility performance—Implications for music pedagogy in high-consequence industries
Authors: Bruder Alexandra L. , Gururaja Akash K. , Rothwell Clayton D. , Baillargeon Suzanne A. , Shotwell Matthew S. , Edworthy Judy R. , Schlesinger Joseph J.
Published: November 2022

In high-risk domains, accurate and timely communications while multitasking are necessary for safety and efficiency. Complex musical/acoustic environments cause hindered communication and awareness. This study used an audio-visual multi-tasking paradigm that examined speech intelligibility and if formal music training (FMT) can mitigate these challenges. Twenty-five students (16F/9M) from Vanderbilt University participated with varying levels of FMT: no FMT, 1–3 years, 3–5 years, and 5+ years of FMT. The study found that the degree of FMT significantly impacted non-response (p-value < 0.001). Among participants with no FMT, the presence of background music increased the odds of non-response by 1.5-fold (95% CI: 0.95, 2.37), conversely, participants with 5+ years of FMT had no decrease (OR: 0.97, 95% CI: 0.69, 1.36), showing that non-response in the presence of music worsens with each subgroup until 5+ years of FMT. The accuracy for all groups was similar (p = 0.74) and the background music decreased accuracy for all groups (OR: 0.67, 95% CI: 0.58, 0.76). Although levels of accuracy were similar for all, the 5+ FMT group responded less frequently, which may indicate increased working memory (i.e., phonological loop) and meta-cognition, a valuable skill in high-risk industry. Future research can explore the pedagogy of musical training.
Emotion equalization app: A first study and results
Authors: Law Man Hei , Horner Andrew B. , Leung Hoi Ting
Published: November 2022

In recent years, there is an increasing trend of mental health issues in society. It is important to identify mental first aid strategies that can be applied at an early age, whether emotional issues have been diagnosed or have yet to be found. Music has tremendous potential impact on changing emotional states since it can distract listeners from rumination on negative thoughts and engage them in a moment of musical enjoyment. This paper presents a new emotion equalization app that incorporates validated diagnosis tests (PHQ-9 and GAD-7) and an emotion measuring tool (SAM) for establishing a personalized therapy treatment using emotion rebalancing methods. By determining the emotional state of the user, songs are chosen and sequenced in a playlist using one of three proposed methods (consoling, relaxing, and uplifting) with a baseline method (random). With this systematic generation of playlists, the app can be used for personalized therapeutic treatment even for users without music background. In our experiment, the results showed positive changes in listeners’ valence levels while there was no significant change in arousal. Furthermore, the relaxing and uplifting methods showed a significant effect on moving listeners from negative to more positive emotional states.
A comparison of the emotional characteristics of western orchestral sustaining musical instrument families with different pitch and dynamics
Authors: Chan Hiu Ting , Chang Bing Yen , Horner Andrew B. , Law Man Hei
Published: November 2022

Recent research has shown that the emotional characteristics of the bowed strings and brass change with different pitch and dynamics. This work compares how pitch and dynamics influence their characters in the western orchestral sustaining musical instruments. We conducted listening tests where listeners gave absolute judgements on the sounds over ten emotional categories and analyzed the data with logistic regression. For pitch, the categories Happy and Heroic had an arched shape that peaked at C6. Romantic, Calm, and Shy increased until C4 and decreased afterwards. Comic and Mysterious did not shown a clear common trend with pitch. Angry and Scary had a U-shape that was slightly stronger at the highest pitch, while Sad decreased with pitch. For dynamics, Happy, Heroic, Comic, and Angry were stronger for loud notes, while Romantic, Calm, Mysterious, Shy, and Sad were stronger for soft notes. For Scary, loud and soft notes were about the same. In the bowed strings and woodwinds, pitch and dynamics had about an equally important effect on the emotional characteristics, while pitch had a more important effect than dynamics in the brass. For the bowed strings, brass, and woodwinds, the particular instrument was more of a secondary factor though still important.
Evaluation of a gamma power, wrapped normal phase model for vertical and slanted atmospheric sound propagation
Authors: Kamrath Matthew J.
Published: November 2022

As sound propagates through the atmosphere, turbulence causes fluctuations in the signal power and phase. These fluctuations complicate the signal processing required to detect, locate, and identify elevated sources. This presentation evaluates a model that assumes a gamma distribution describes the power and a wrapped normal distribution describes the phase. The gamma distribution approximates a log-normal distribution when the normalized power variance is small compared to one and an exponential distribution when the normalized power variance is one. The wrapped normal distribution approximates a normal distribution when the phase variance is small and a uniform distribution when the phase variance is large. In 2018, we measured vertical and slanted sound propagation at the National Wind Technology Center (NWTC). The ground-borne source emitted tones in the range 600–3500 Hz, and several microphones were mounted to a meteorological tower up to 130 m high. Overall, the gamma power, wrapped normal phase model accurately approximated the NWTC data across a wide range of scattering regimes. This presentation also discusses the largest discrepancies.
An investigation of interference between electromagnetic articulography and electroglottography
Authors: Goel Jessica , Masapollo Matthew , Wayland Ratree , Sengupta Rahul , Shamsi Allen , Hegland Karen W.
Published: November 2022

The present study tested whether there is cross interference between state-of-the-art electromagnetic articulography (EMA) and electroglottography (EGG) during the acquisition of kinematic speech data. In Experiment 1, we calibrated EMA sensors with and without EGG electrodes present in the EMA field. In Experiment 2, EMA was used to record lip, tongue, and jaw movements for one male talker and one female talker, with and without simultaneous EGG recording. Collectively, the results provide no evidence of signal artifacts in either direction, suggesting that current EMA and EGG technology can be combined to reliably assess laryngeal and supralaryngeal motor coordination in speech.
Anatomical measures of the vocal tract in children ages 5 and 6
Authors: Diekhoff Megan , Lulich Steven M.
Published: November 2022

At the same time young children experience rapid physical growth, they are faced with the challenge of mastering the complexities of speech production. Capturing the dimensions of the vocal tract during early childhood is a crucial step in characterizing early speech acoustics and speech motor control. The present study partially replicates measures of the vocal tract first employed in previous studies. Magnetic resonance images (MRI) were obtained from two 5-year-old and six 6-year-old children. Anatomical measurements of the vertical vocal tract (VT-V), posterior cavity length (PCL), anterior cavity length (ACL) and overall vocal tract length (VTL) are reported for each child. Results are consistent with previous findings, and are foundational for a larger, stratified longitudinal study aiming to characterize the development of individuals’ vocal tract anatomy between 5 and 9 years of age. [Work supported in part by NSF.]
SpeakerPool: A remote speech data collection platform
Authors: Schnoor Tyler T. , Tucker Benjamin V.
Published: November 2022

The collection of speech production data for academic use has traditionally been carried out by recording participants in-person. While certain types of research require traditional data collection methods, many factors, such as distance and world events, make remote collection a valuable alternative for other types of research. Despite the existence of capable technologies and the advantages of remote collection methods, to the authors' knowledge there is no freely accessible, reusable, and research-oriented platform for the remote collection of speech production data. We aim to address this with SpeakerPool: a web application that, in addition to providing an easy-to-use recording interface for participants, has built-in functionalities for the automation of many tasks. Users are able to access SpeakerPool regardless of platform using modern web browsers on both mobile and non-mobile devices. This greatly reduces compatibility limitations and bypasses the need to download software. In the present study, we discuss the general advantages and disadvantages of remote speech data collection and investigate the usefulness of SpeakerPool by collecting and analyzing a pilot data set of Malagasy speech.
Developing a voice monitoring smartphone app: Acoustic acquisition and processing considerations
Authors: McKenna Victoria S. , Llico Andres F. , Friedman Aaron , Shanley Savannah N. , Talavage Thomas , Bamford Leigh M.
Published: November 2022

With the advent of smartphone technology, there has been an increase in at-home health monitoring. Yet, there are few applications (apps) available to track voice acoustics for those with voice disorders. Therefore, we completed two investigations into the acquisition and processing of the acoustic signal to help develop a voice monitoring app. Study 1: We investigated how microphone distance and phone tilt impact the accuracy of acoustic measures of voice. A total of 58 participants with (n = 47) and without (n = 11) voice disorders completed speech tasks of sustained vowels and the rainbow passage. Concurrent recordings were collected using the participant’s phone, as well as a stationary headset microphone for comparison. We determined that the voice measures of fundamental frequency (Hz), voicing duration (seconds), and cepstral peak prominence (dB) were impervious to phone distance and tilt. Study 2: Focusing on the three acoustic measures from study 1, we investigated the correspondence between acoustic measures attained with clinically available software (e.g., Praat) and those from our own lab-developed algorithms specialized for on-app processing. Preliminary results show strong relationships (r > .90) between the different processing techniques. Further work is needed to understand how participant-specific factors (age, dysphonia severity) may improve algorithm accuracy.
The acoustic profiles of vocal emotions in Japanese: A corpus study with generalized additive mixed modeling
Authors: Wang Fenqi , Deng Delin , Wayland Ratree
Published: November 2022

This study investigated the vocal emotions in Japanese by analyzing acoustic features from emotional utterances in the Online Gaming Voice Chat Corpus with Emotional Label (Arimoto and Kawatsu, 2013). The corpus contains the recorded sentences produced in 8 emotions by four native Japanese speakers who are professional actors. For acoustic feature extraction, Praat script ProsodyPro was used. Principle component analysis (PCA) was conducted to evaluate the contribution of each acoustic feature. In addition, a linear discriminant classifier (LDA) was trained with the extracted acoustic features to predict the emotion category and intensity. A generalized additive mixed model (GAMM) was performed to examine the effect of gender, emotional category, and emotional intensity on the time-normalized f0 values. The GAMM’s results suggested the effects of gender, emotion, and emotional intensity on the time-normalized f0 values of vocal emotions in Japanese. The recognition accuracy of the LDA classifier reached about 60%, suggesting that although pitch-related measures are important to differentiate vocal emotions, bio-informational features (e.g., jitter, shimmer, and harmonicity) are also informative. In addition, our correlation analysis suggested that vocal emotions could be conveyed by a set of features rather than some individual features alone.
Fearless steps Apollo: Advancements in robust speech technologies and naturalistic corpus development from Earth to the Moon
Authors: Hansen John H. , Joglekar Aditya , Chandra Shekar Meena
Published: November 2022

Recent developments in deep learning strategies have revolutionized Speech and Language Technologies(SLT). Deep learning models often rely on massive naturalistic datasets to produce the necessary complexity required for generating superior performance. However, most massive SLT datasets are not publicly available, limiting the potential for academic research. Through this work, we showcase the CRSS-UTDallas led efforts to recover, digitize, and openly distribute over 50,000 hrs of speech data recorded during the 12 NASA Apollo manned missions, and outline our continuing efforts to digitize and create meta-data through diarization of the remaining 100,000hrs. We present novel deep learning-based speech processing solutions developed to extract high-level information from this massive dataset. Fearless-Steps APOLLO resource is a 50,000 hrs audio collection from 30-track analog tapes originally used to document Apollo missions 1,7,8,10,11,&13. A customized tape read-head developed to digitize all 30 channels simultaneously has been deployed to expedite digitization of remaining mission tapes. Diarized transcripts for these unlabeled audio communications have also been generated to facilitate open research from speech sciences, historical archives, education, and speech technology communities. Robust technologies developed to generate human-readable transcripts include: (i) speaker diarization, (ii) speaker tracking, and (iii) text output from speech recognition systems.
Noise from above: A summary of studies regarding the perceived annoyance due to impact sounds
Authors: Mueller-Trapet Markus , Skoda Sabrina , Choi Young-Ji , Batista da Cunha Iara , Mahn Jeffrey
Published: November 2022

To support efforts of introducing an impact sound requirement into the National Building Code of Canada (NBCC), the National Research Council of Canada has initiated a long-term research project. In cooperation with the Hochschule Duesseldorf in Germany and Kangwon National University in Korea, several listening tests were performed to investigate the annoyance due to impact sound as it is perceived by building occupants, and how this annoyance relates to the results of standardized laboratory measurements. In this contribution, the different listening test setups will be described and compared. Tests were performed in the laboratory using loudspeakers, headphones, and also with a Virtual Reality headset. In addition, an online listening test was launched to expand the reach of such studies to the general population. The results will be summarized and discussed regarding appropriate rating methods. The goal of these studies is to gain a better understanding of the relevant factors that affect the perceived annoyance, such as the impact source type and the dominant frequency range, but also how the test environment influences the results.
Investigating of the impact of biommetic pinna dynamics on sonar tasks in natural environments
Authors: Goldsworthy Michael , Osman Salwani , Patterson Grant , Müller Rolf
Published: November 2022

Bats are known to perform incredible feats using their echolocation abilities, which include natural tasks, such as navigation through foliage and hunting prey, as well as tasks they have been trained to perform, such as classification of man-made objects. Much work has been done to engineer biomimetic systems that can perform these and similar tasks in a comparable way to bats. Biomimetic sonar devices have performed tasks such as identifying a geographic location, object classification, and foliage gap finding. Particular species of bats (notably those of the families Hipposideridae and Rhinolophidae) use rapid ear motion while making sonar calls, and the full effect and purpose of this motion is not fully understood. Our research goal is to perform sonar tasks with a biomimetic sonar head capable of both static and dynamic ear motion and investigate the effect of dynamic ear motion on captured echoes and performance on tasks. To this end, we have collected echo data in natural habitats with dense tropical vegetation in Brunei on the island of Borneo. Tasks currently under investigation include location identification and detection of man-made objects in foliage, and are performed by deep learning classifiers trained on echoes taken by the biomimetic sonar device.
Autonomous localization and mapping based on biomimetic sonar in natural environments
Authors: Patterson Grant , Wang Ju , Goldsworthy Michael , Osman Salwani , Hinson Adam , Müller Rolf
Published: November 2022

Bats navigating in dense vegetation based on biosonar have to obtain the necessary sensory information from “clutter echoes,” i.e., echoes that are superpositions of contributions of many reflecting facets (e.g., leaves). Since the locations and reflective properties of the individual facets are unknown, clutter echoes have to be treated as random signals that can neither be predicted nor—under most practical circumstance—be replicated. Nevertheless, prior research has shown that deep neural networks are capable of extracting fairly precise location information from clutter echoes. This raises the question whether clutter echoes could be used to provide navigational guidance in a conventional simultaneous localization and mapping (SLAM) framework, which is to a large extent dependent on precise and deterministic measurement to generate a localized map. Our hypothesis is that biomimetic sonar echoes indeed contain the information that is necessary support to local path planning, which can be utilized by a suitable deep learning architecture and training process. To investigate this issue, we have collected data in natural, heavily vegetated environments using a biomimetic sonar head that mimics the periphery of the biosonar system in horseshoe bats. The annotation of the data and the network training process is currently undergoing.
A bioinspired robot for investigating biosonar guidance of flapping flight in bats
Authors: Tyler Adam , Blackman Trinity , Sequeira Yohan , Beiter Benjamin C. , Müller Rolf
Published: November 2022

Investigating how bats manage to control their complex flight apparatus using streams of biosonar echoes as inputs with an approach based on biomimetic robotics, we have designed a bioinspired flapping robot that replicates some of the features of the flight apparatus of bats: In particular, it incorporates a mechanism to translate one degree of freedom from a motor into flapping as well as folding of the wings. Throughout the flapping cycle, the wings are folding and unfolding continuously in a way that achieves maximum upward lift. Similarly to a bat, a wing membrane is stretched over the wings and pulled taut. The design is primarily 3-D printed to reduce weight and allow for rapid prototyping. Future iterations of the robot will continue to reduce the weight and add more degrees of freedom to enable greater maneuverability in the air. After flight has been achieved, acoustics in the form of ultrasonic microphones will be implemented on the robot for further navigational capabilities. It is important to optimize the robot for the maximum amount of lift while keeping the robot as light as possible to allow for a greater capacity for acoustics equipment while still maintaining the ability to fly.
Ambient sound observations from beamformed horizontal array data in the Pacific Arctic
Authors: Cushing Colby W. , Sagers Jason D. , Ballard Megan
Published: November 2022

Changes in the Arctic environment with regard to declining sea ice and changing oceanography are expected to alter the ambient sound field, affecting both the sound generating processes and the acoustic propagation. This talk presents acoustic recordings collected on the 150-m isobath on the Chukchi Shelf during the Canada Basin Acoustic Propagation Experiment (CANAPE), which took place over a yearlong period spanning October 2016 to October 2017. The data were recorded on a 52-channel center-tapered horizontal line array and adaptively beamformed to quantify the azimuthal directionality in long-term trends ambient sound under 1200 Hz as well as track specific sound events as they travel through space over time. The acoustic data were analyzed in the context of wind speed and satellite imagery to identify the dominant sound generation mechanisms. Automated identification system (AIS) data were also incorporated to determine sources of ship generated sound and seismic profiler activity observed in the acoustic recordings. This talk will provide an overview of the long-term trends and describe a subset of results from the beamforming. [Work Supported by ONR.]
Modelling of sound propagation across the Arctic Ocean using oceanographic fields and oceanographic data
Authors: Storheim Espen , Sagen Hanne , Dzieciuch Matthew A. , Worcester Peter F.
Published: November 2022

During the coordinated arctic acoustic thermometry experiment (CAATEX), two acoustic sources transmitted 35 Hz binary m-sequences in a yearlong experiment. The signals were transmitted across the Arctic Ocean and detected at distances up to 2700 km. The aim was to make measurements similar to those carried out in 1994 and 1998, to investigate the changes in sound propagation due to changes in the ocean temperature, ocean stratification, and thinning of the sea ice. Changes in propagation conditions over the last decades were investigated using time-series of data from ocean reanalysis, as well as available oceanographic data along the transect. Range-dependent fields were constructed and used as environmental input to acoustic models to produce time series of arrival times and vertical arrival structure. This approach allows for an examination of the sensitivity of low-frequency sound propagation to both vertical and large-scale horizontal changes in the ice-ocean environment. The predicted time series of acoustic travel times and arrival structure will be presented and compared with the observations.
Narrowing the distribution of ultrasound image quality using machine learning and deep learning
Authors: Khan Christopher , Pan Ying-Chun , Byram Brett
Published: November 2022

Ultrasound image quality varies substantially across different subjects. In some cases, this means ultrasound images are non-diagnostic. Overcoming these non-diagnostic exams is a common goal for advanced ultrasound beamforming algorithms. Recently, new beamforming approaches using machine learning and deep learning have been proposed by a number of groups to overcome ultrasound’s image quality issues. Our group has proposed several methods relying on both machine learning and deep learning approaches. We will also show how physics-based machine learning methods can lead directly to deep learning methods, and we can use the development and performance of these methods to generate insight into the underlying structure of ultrasound data. We will also show that rather than leading to artificial gains, deep learning methods can be used to actually increase the available information in the form of improved dynamic range compared to delay and sum beamforming. The improvement is 15–20 dB, and we can achieve this improvement in both clean and highly cluttered data. Finally, we will show that ultrasound beamformers can be trained with unlabeled in vivo data in order to learn the underlying distribution of clutter in particular in vivo scenarios (e.g. echocardiography). This leads to improvements in imaging performance and can be used to generate insight into the interaction of different sources of image degradation in vivo.
Split-step simulations of sonic boom propagation beyond the lateral cutoff in a turbulent atmosphere
Authors: Carr Alexander N. , Lonzaga Joel B. , Miller Steven A.
Published: November 2022

Recent flight tests during the Quiet Supersonic Flights 2018 (QSF18) study reported sonic booms heard outside of the primary carpet region. In the absence of turbulence, the lateral cutoff region separates the primary sonic boom carpet from the shadow zone, where the sonic boom signal experiences significant attenuation. However, when turbulence is present in the atmospheric boundary layer (ABL), additional scattering of the sonic boom to the shadow zone region occurs. A method is presented for simulating sonic boom propagation in a turbulent atmospheric boundary layer beyond the lateral cutoff region into the shadow zone. A split-step method is used to integrate a partially one-way equation for the acoustic pressure. Inhomogeneous turbulence, representative of the ABL, is generated in the computational domain with a Fourier synthesis approach. Distributions of several loudness metrics in the shadow zone region for a sonic boom N-wave and a shaped boom are examined. Increasing both turbulence root-mean-square velocity and integral length scale are found to increase the average loudness of booms in the shadow zone. (This research is supported by the Commercial Supersonic Technology Project of the National Aeronautics and Space Administration under Grant No. 80NSSC19K1685.)
Sound field reconstruction in urban environments: Application to enhance mapping of urban microspaces
Authors: Denis Max , Gaye Samba , Mandjoupa Lirane , Davis Dorian , An Justin , Mahmoud Wagdy , wang lei
Published: November 2022

In this work, reconstruction techniques for the spatial interpolation and extrapolation of sound fields in urban environments are presented. Gaussian processes are generally used for sound field reconstruction from limitedly observations of isotropic acoustic fields. However, this model is often not applicable for the anisotropic urban environments including urban street canyons and enclosed spaces, when the complexity of the sound field is high in the mid-frequency regime, unless diffusely reflecting boundaries are assumed. Two different techniques are compared for reconstructing the sound field: the least-squared method and the Kirchhoff-Helmholtz integral equation method. Of particular interest is the reconstruction of the sound field with a minimal number of irregularly and arbitrarily distributed microphone measurements. Therefore, the techniques will not require knowledge of the microphone positions. A successive series approximation approach is presented to enhance the microscale prediction of the Kirchhoff-Helmholtz integral equation method. The sound field reconstruction results from limited urban environment observations for both methods are presented and discussed.
Estimating sonic boom metrics across a community using a Kalman filter
Authors: Lympany Shane V. , Page Juliet A.
Published: November 2022

As part of the Quesst mission, NASA will fly the X-59 aircraft over selected communities to evaluate community responses to low-intensity sonic booms. The purpose of these community tests is to determine the dose-response relationship between the noise exposure metrics and the community response. The independent variables for the dose-response relationship are the noise exposure metrics experienced by survey respondents within the community. Two sources of noise exposure metrics are available in each community: measurements at sparse locations throughout the community, and calculations from propagation models across the community. Both the measurements and calculations are subject to uncertainty. A Kalman filter is proposed to combine the measured and calculated noise exposure metrics to obtain the best estimate of the true noise exposure metrics across the community. The noise exposure metrics estimated by the Kalman filter have lower uncertainty than either the measured or calculated noise exposure metrics alone. Simulations demonstrate that the Kalman filter produces a more accurate estimate of the true noise exposure metrics than other noise estimation methods.
Numerical analysis of the limits of effective medium theory for nonlinearly propagating dispersive waves
Authors: Muhlestein Michael B. , Dunn Kyle G.
Published: November 2022

Acoustic metameterials are an increasingly popular approach to control both linear and nonlinear sound propagation. In this approach, heterogeneous structures are engineered to behave as predetermined continuous media. A key requirement for a system to be accurately approximated as a homogeneous material for wave motion is that the smallest length scale of the waveform be much larger than any length scale associated with the microscale structure of the system. However, the fact that the characteristic length scales of a finite-amplitude waveform can change due to nonlinear effects means that care must be taken when analyzing such signals in an acoustic metamaterial. This talk presents recent work toward understanding the breakdown of effective medium theory as finite-amplitude waves propagate in a heterogeneous system and weak shocks or solitons begin to form. A finite-difference time-domain code was used to model the propagation of a pulse of sound in a one-dimensional propagation domain using both a full description of the system and an effective-medium description accounting for effective mass density, compressibility, coefficient of nonlinearity, and dispersion. The difference between the solutions of the two models provides a method by which one can estimate the error associated with using effective properties.
Resonant ultrasound spectroscopy: How much information lies in higher frequencies
Authors: Farzbod Farhad
Published: November 2022

Resonance ultrasound spectroscopy (RUS) is a well-established experimental technique for measuring all the elastic properties and a few anelastic properties of a material. A sample with known geometry is excited to vibrate in a wide range of frequencies, and its resonant frequencies are detected. The resonant frequencies depend on elastic constants; as such, a complete set of elastic constants can be extracted from the resonant frequency values. In this work, we investigate first the sensitivity of resonant frequencies to some of the elastic constants, and second, how much data are in the resonant frequencies as they go higher. It has been speculated that the higher modes have more info about the off-diagonal elastic constants and shear modes of vibrations. We will investigate this hypothesis and study resonant frequencies' limiting behavior.
Do cochlear implant users experience the same amplitude modulation rates in each ear?
Authors: Soleimanifar Simin , BK Prajna , Aronoff Justin M.
Published: November 2022

Cochlear implant (CI) users often produce different vocal fundamental frequencies (F0s) when using the left versus the right CI device. Since pitch perception and production are linked, differences in produced F0s likely indicate differences in perceived vocal pitches for the same F0 when using different ears. One possible explanation for different pitch perceptions with each ear is that, while F0s are typically encoded in the amplitude modulations (AM) of electrical stimulation, the resulting temporal pitch may differ for each ear. This study aimed to investigate if CI users perceive the same AM rates as different pitches with each ear. Five CI users participated in an AM pitch matching study using place-pitch-matched electrodes in the two ears. They were given two sounds with AM and asked to turn a dial, changing the AM rate in one ear to make the pitch of the second sound similar to the pitch of the first sound. The preliminary results showed that some participants perceived different pitches in the two ears for the same AM rate, and some did not, suggesting that the same AM-encoded F0s may be perceived as a different vocal pitch, but only for some CI users.
Spatial relationships between interaural differences in a room
Authors: Hartmann William
Published: November 2022

The interaural ratio, as it occurs for a human head in a room, can be represented by a filter with a complex transfer function of the spatial location of the head. The log of this transfer function has real and imaginary parts, respectively, the interaural level difference (ILD) and the interaural phase difference (IPD). Because the filter is causal, the ILD and IPD spatial functions are Hilbert transforms of each other if the interaural filter is a minimum phase function of the head location. Interaural differences for a spherical “head” with tiny probe microphones, separated by a head diameter of 17.5 cm, were measured by Mr. Zane Crawford in an empty room having a volume of 63 $m∧3$ and a reverberation time of 0.4 s. The head was moved in increments of 2.54 cm over a two dimensional grid 102 cm by 23 cm. Measurements at 250 Hz showed that the ILD and IPD were almost perfectly related by Hilbert transforms. Measurements at 500 and 1000 Hz showed increasing deviations. Because a function is orthogonal to its Hilbert transform, the ideal ILD is orthogonal to the IPD. Therefore, at locations where the ILD is the most stable function of space, the IPD is the most unstable and vice versa.
Assessing speech communication in the operating room
Authors: Viswanathan Navin , Rudy Paul , Krishnan Tara , Brommelsiek Margaret , Sutkin Gary
Published: November 2022

Smooth communication in the operating room (OR) is essential. However, its acoustic environment is typically composed of machine and human caused sounds such as patient temperature monitoring devices, systems, waste management systems, and irrelevant conversations that impede speech communication. These challenges are exacerbated by the need for combinations of facial protective equipment (FPPE) that both attenuate critical speech information as well as obviate relying on visual information for understanding speech. In order to faithfully capture the challenges to speech perception in this environment, we first recorded various interfering sounds based on a qualitative study of over 59 surgeries across different specializations. We analyzed their acoustic characteristics and obtained subjective measures of perceived interference from 60 surgical team members who all worked in the OR. In a follow up study, we assessed the acoustic consequences of different facial ppe combinations on produced speech. In both studies, we identified critical impediments to smooth OR communication. These include high decibel levels of interfering sounds, attention engaging irrelevant speech, and substantial attenuation of speech frequencies when using typical FPPE combinations. These studies constitute our preliminary steps to identifying and alleviating speech perception challenges in the OR.
Vocal health for mask-wearing healthcare providers
Authors: McKenna Victoria S. , Gustin Renee L.
Published: November 2022

With the onset of the COVID-19 pandemic, healthcare providers are now required to wear face masks throughout the day. However, masks impact communication by creating a barrier to sound. Our previous studies show that masks attenuate mid-to-high-range frequency content and reduce vowel articulatory space. Mask-wearing healthcare workers also report significant increases in vocal effort compared to unmasked speech, as well as increased vocal effort at the end of their workday. Increased vocal effort co-occurred with a reduction in relative fundamental frequency (RFF) offset cycle 10—an acoustic indicator of vocal effort and laryngeal tension. With this in mind, we developed recommendations to help overcome some of the challenges of masked communication, with a specific focus on vocal health maintenance. A small pilot study in mask-wearing healthcare providers found that providers were able to learn and recall vocal health information with >90% accuracy over one week and implement 4 out of 6 vocal recommendations into their workday. RFF offset cycle 10 improved (Cohen’s d = 0.25) following strategy implementation. More research in a larger group of providers is needed to understand the long-term effects of mask-wearing on vocal health, and the behavioral strategies healthcare workers can use to prevent voice problems.
Automatic speech recognition for unmanned aerial vehicles
Authors: Bohouta Gamal
Published: November 2022

Unmanned aerial vehicles (UAVs), also known as unmanned aerial systems (UASs), are quickly becoming a ubiquitous technology, poised to enter some key large-scale markets in the very near future. Fleets of such vehicles will be required in these large-scale deployments for commercial, industrial, and emergency response, along with the ability to efficiently control these fleets. Voice control and communication between human operators and these fleets will become imperative. This paper explores the framework for building an automatic speech recognition (ASR) use to the control of unmanned aerial vehicles (UAVs). The ARS system will be used by Aeronyde Corporation to fully-autonomous fleets with minimal human intervention. Aeronyde Corporation is working to shift and advance the current industry thinking of unmanned platforms from Remotely Piloted Aircraft (RPA) to fully-autonomous fleets with minimal human intervention. The Aeronyde Avionics package enables a single operator to control and monitor missions of many drones in real time anywhere in the world. The “1 Pilot – Many Drones” approach to aerial data collection is revolutionary for Big Data aggregation and analytics of the 4th Industrial Revolution. Multi-UAV autonomous aerial systems will transform data acquisition for many commercial applications, including: agriculture and forestry, railroad inspections, pipeline inspections, powerline inspections, windmill inspections, terrain mapping, search and rescue, firefighting and police work, and border patrol.