bluuebunny/crossref_metadata_2025 huggingface dataset:
Suitability of self-recordings and video calls: Vowel formants and nasal spectra
Authors: Freeman Valerie , De Decker Paul , Landers Molly
Published: December 2020

When the COVID-19 pandemic halted in-person data collection, many linguists adopted new online technologies to replace traditional methods. These included VoIP video conferencing apps like Zoom, which allow live interaction with participants, as well as user-led options in which participants record themselves using personal computers or smartphones and then email or otherwise transfer the sound files to researchers online. This study evaluated the suitability of such recordings for phonetic analysis of vowel space configurations, mergers, and nasalization by comparing simultaneous recordings from several popular personal devices (Macbook, PC laptop, iPad, iPhone, Android phone) and video call apps (Zoom, Skype, Teams) to those taken from professional equipment (H4n field recorder, Focusrite with table-top microphone). All personal devices and apps conveyed vowel arrangements and nasalization patterns relatively faithfully (especially laptops), but absolute measurements varied, particularly for the female speaker and in the 750-1500 Hz range, which affected the locations (F1xF2) of low and back vowels and reduced nasalization measurements (A1-P0) for the female's pre-nasal vowels. Based on these results we assess the validity of remote recording using these devices and offer recommendations for best practices for collecting high fidelity acoustic phonetic data from a distance.
How do listeners use context frequencies in tone-scramble tasks? Evidence from a web-based experiment
Authors: Waz Sebastian , Chubb Charles
Published: December 2020

When listeners try to discriminate rapid pure-tone sequences (“tone scrambles”) whose frequencies come from a major set (G5, B5, D6, and G6) versus a minor set (G5, B♭5, D6, and G6), most (≈70%) perform near chance (Chubb et al., 2013). The rest perform near ceiling. The variation in performance is largely explained by possession of a single processing resource (Dean and Chubb, 2017). Does this resource grant acuity for the target frequencies (B5 and B♭5) selectively, or does it underlie some context-sensitive (G5, D6, and G6) musical ability? To investigate, we asked listeners to perform the discrimination as stimuli were translated randomly from trial to trial in log frequency. Listeners thus needed to use context to succeed. Performance remained well above chance in high-performers. Similar results were found when targets were randomly selected on each trial to be major/minor thirds (B5/B♭5) or sixths (E6/E♭6). We also investigated whether the context tones caused spectral masking of the targets by manipulating the frequency width of the context. We found limited evidence for such masking. The single-resource model explained 66.53% of the variation across all conditions. Since the experiment was administered online, our results may offer recommendations for future web-based psychoacoustic experiments.
Examining spectral and intensity resolution in web-based vocoder simulations of electric hearing
Authors: Beim Jordan A. , Kreft Heather , Oxenham Andrew J.
Published: December 2020

The poor spectral resolution in current cochlear implants contributes to the difficulty implant users face when trying to listen in noisy backgrounds. Recent work examining measures of spectral resolution and speech perception in normal-hearing and cochlear-implant listeners found that the amount of simulated spectral resolution producing similar speech-in-noise performance between groups resulted in poorer performance for the normal-hearing group on spectral-ripple detection and discrimination tasks. The results suggest that simulating poorer spectral resolution alone is not sufficient to explain implant user performance. Spectral-ripple detection performance likely reflects both spectral- and intensity-resolution, but few vocoder simulations utilize implant-like intensity resolution. In this study, a vocoder processing strategy simulating both electric field spread and dynamic range limitations was used to evaluate performance of normal-hearing and cochlear-implant listeners on speech-in-noise and spectral-resolution tasks. Data were collected using a novel online remote testing platform developed implemented with the MATLAB Web App Server. A comparison of results between groups highlights the implications of including psychophysically measured estimates of cochlear-implant performance in acoustic simulations of electric hearing. [Work supported by NIH grant R01DC012262.]
Enhanced loudness perception in ears with reduced peripheral function: A remote psychoacoustic investigation
Authors: Jahn Kelly N. , Hancock Kenneth E. , Maison Stéphane F. , Polley Daniel B.
Published: December 2020

Central gain models of hyperacusis propose that a loss of afferent input drives over-amplification of sound-evoked activity in the central auditory system, leading to enhanced loudness perception. We conducted a remote study aimed at quantifying variation in loudness perception as a function of peripheral auditory status [i.e., summating potential (SP)/action potential (AP) ratio]. To control for the contributions of age and other individual differences, twelve adults with normal hearing and strongly asymmetric SP/AP ratios between ears were recruited from a prior study. Participants completed a battery of self-directed psychoacoustic tests at home using calibrated headphones and tablet computers running custom software. Loudness perception was assessed at a variety of frequencies in each ear using standard clinical assessments [e.g., loudness discomfort levels (LDLs), dynamic range] and more fine-grained assessments of loudness growth as a function of stimulus intensity. While traditional measures of LDL and dynamic range varied widely both within and between subjects, ears with evidence of possible cochlear synaptopathy (high SP/AP ratios) demonstrated elevated loudness perception for intensities in-between threshold and LDL. Detailed assessments of loudness growth across sensation levels may be more sensitive to variation in underlying peripheral neural status than traditional, single-point clinical measures of loudness discomfort.
Identification of unreliable subject data from remote testing
Authors: Shub Daniel E. , Perry Trevor T. , Makashay Matthew J. , Galloza Hector , Brungart Douglas S.
Published: December 2020

The less controlled nature of conducting behavioral testing outside of the typical sound booth and not under the direct observation of the experimenter introduces additional factors that may lead to unreliable data. These factors arise from the environment (e.g., room acoustics and background noise), the participant (e.g., attention, engagement, and understanding of the task), and the testing apparatus (e.g., calibration and network latency). Remote-testing protocols should include features to allow for the detection of unreliable data. To aid in the detection of unreliable data in future remote-testing protocols, we retrospectively examined a large dataset (N > 1000) of speech intelligibility and tone-in-noise detection that was collected over headphones with a tablet-based system in a waiting room environment. The dataset provides the ability to determine the extent to which unreliable data can be detected based on the presence of high levels of background noise during the testing, abnormally short response times, high lapse rates, flat psychometric functions, and patterns in the response sequence. [The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of Army/Navy/Air Force, Department of Defense, or U.S. Government.]
Smart panel with piezoelectric patches connected to adaptive multi-resonant shunts for broadband vibration control
Authors: Gardonio Paolo , Konda Rodrigues Gabriel , Dal Bo Loris , Turco Emanuele
Published: December 2020

This paper presents a simulation study on the broadband control of flexural vibration of thin panels equipped with piezoelectric patches connected to adaptive multi-resonant shunts. The study considers the broadband flexural response of a thin rectangular aluminum panel exposed to a spatial and time stochastic excitation. The panel is equipped with thin square piezoelectric patches connect to shunts encompassing multiple parallel branches formed by RLC components connected in series. The capacitance C of each branch is kept fixed, whereas the inductance L and resistance R are adapted so as each branch maximizes the vibration power absorption from the resonant response of a specific flexural mode of the panel. The study proposes an on-line tuning approach, where the N-branches of each shunt are adapted sequentially to maximize the vibration absorption from the resonant responses of N neighbor flexural modes. The vibration power absorption of each branch is estimated from the electric power absorbed by the shunt. In this way a local tuning system can be implemented, which adapts on-line the shunts to control the flexural response produced by a group of flexural modes of the panel resonating in a given frequency band.
Experimental determination of wavenumber dispersion for active adaptable acoustic metamaterials
Authors: Stearns Aaron , Beck Benjamin S.
Published: December 2020

Acoustic metamaterials are composite materials exhibiting effective properties and acoustic behavior not found in traditional materials. Through periodic subwavelength resonant inclusions, acoustic metamaterials enable steering, cloaking, lensing, and frequency band control of acoustic waves. A common drawback of acoustic metamaterials is that the properties are limited to narrow frequency bands. Investigation of practical active and adaptable acoustic metamaterials is valuable in achieving wider operation frequency bands. Numerical predictions of wave propagation behavior in acoustic metamaterials are commonly presented in the form of elastic band structure diagrams. In previous work, the complex wavenumber dispersion properties of the metamaterial medium were proposed as optimization objectives for obtaining optimal adaptable metamaterial unit cell configurations for vibration reduction. To verify numerical wavenumber predictions, the current work presents an experimental method to obtain the wavenumber dispersion. First, the metamaterial beam is excited with a broadband pulse. Time domain responses are recorded at many locations on the structure. The resulting time series data is processed with a two dimensional Fourier transform. The result is a wavenumber versus frequency plot. The procedure is useful for plate and beam type metamaterial structures wherein local resonances and active inclusions cause wave attenuation if the above experimental procedures can be feasibly carried out.
Speech perception in deaf and hard of hearing Arabic-speaking children
Authors: Rosenhouse Judith
Published: December 2020

The rate of Deaf and Hard of Hearing (DHH) people is relatively large in native Arabic speakers in Israel. However, Arabic assessment tools are scarce. The present study reports the procedure of developing two speech perception assessment tools, which are used for hearing loss diagnosis, hearing aids fitting, cochlear implant mapping, and evaluation of progress following rehabilitation intervention. Our closed set test “Arabic Picture Speech Pattern Contrast” (ArPiSPAC), and word perception open-set test, “Arabic AB” (ArAB), were administered to 34 children with moderate to profound sensorineural hearing loss, hearing aids users, aged between 4;5—8;11. In addition, the ArPiSPaC was administered to 38 hearing children, aged between 2;6-5;5 in order to obtain a developmental hierarchy. For DHH participants, the findings showed that vowel contrasts were better perceived than consonants, and articulation manner was better perceived than articulation place. The hearing participants' phonological perception hierarchy differed in some interesting features from that of the DHH children. The mean percent of phoneme perception by DHH was M = 60.53%, (SD = 23.87), and the mean percent of word perception was M = 18.5%, (SD = 15.68). Voicing and pharyngealization contrasts revealed the largest Pearson correlation for phoneme and word perception.
A real-time wavelet-based algorithm for improving speech intelligibility
Authors: Chen Yijia , Wan Yuxuan , Sim Keegan Y. , Zheng Jiakun , Chau Eugene , Chau Kevin
Published: December 2020

Presently reported is a wavelet-based algorithm to improve speech intelligibility. The speech signal is split into frequency sub-bands via a multi-level discrete wavelet transform. Various gains (or attenuations) are applied to the sub-band signals before the signals are recombined to form a modified version of the speech signal. Dynamic range compression then follows to control the peak amplitude. The sub-band gains are adjusted while keeping the overall signal energy unchanged, and the speech intelligibility under simulated hearing loss conditions and various background interferences such as babble, music and machine noises is evaluated objectively and quantitatively using Google Speech-to-Text transcription. For both English and Chinese speech, intelligibility is enhanced, and the transcription accuracy can increase by over 60 percentage points by reallocating the audio energy from low to mid and high frequency sub-bands, effectively increasing the consonant-to-vowel intensity ratio. This is reasonable since the consonants are relatively weak and of short duration, and are therefore the most likely to become indistinguishable in the presence of background disturbances or high frequency hearing impairments. The proposed algorithm is implementable in real-time and simpler than others. Potential applications include speech transmission, hearing aids, machine listening, and a better understanding of speech intelligibility.
Uvular rhotic weakening in Yiddish adjectival suffixes
Authors: Tabachnick Guy
Published: December 2020

In traditional Yiddish dialects, the presence versus absence of word-final rhotics after unstressed [3] in adjectival suffixes carries a heavy functional load, making distinctions of gender, number, and case. Belk et al. (2019) note that some Yiddish speakers with uvular rhotics do not fully articulate them word-finally, endangering this crucial distinction and perhaps contributing to the loss of gender and case in the Yiddish of contemporary Hasidic communities. This study analyzes adjectival endings in publicly available recordings of four speakers with uvular rhotics. The majority of speakers generally do not produce an audible [R] or [] before consonants, but for these speakers, an underlying rhotic conditions lower F1 and sometimes higher F2 in the pre-rhotic vowel [3]. These formant differences tend to be relatively consistent over the course of the vowel, suggesting that they are phonologized, rather than a phonetic effect due to coarticulation with a following uvular rhotic whose articulation may be covert. Word-final [3] similarly exhibits lowered F1 and higher F2 before a word starting with [R] or a dorsal fricative [x/ü], suggesting that coarticulation with a following dorsal is the phonetic precursor to the phonological effect observed for underlying rhotics.
Syllable shape effects on temporal aspects of the Danish stød
Authors: Pena Jailyn M.
Published: December 2020

Danish phonologically contrasts modal phonation with “stød,” a type of nonmodal phonation related to creaky voice (Fischer-Jørgensen, 1989). Stød (?) is licensed in a syllable by either a long vowel or a vowel + sonorant sequence (CV:?(Obstruent/Sonorant), CVS?). Previous research noting high inter- and intra-speaker variability in stød realization has led researchers to claim that temporal aspects of stød production are random and not under speakers' control (Grønnum & Basbøll, 2007). In contrast, this study provides novel evidence that, overall, stød onset is timed with respect to syllables' rime midpoint and stød offset with respect to sonorant rime offset in monosyllabic words, though differences based on rime content persist across word types. 10 native Danish speakers were recorded reading sentences with embedded monosyllabic, stød-bearing words (CV:?(O/S), CVS?), and stød durations were marked. Comparison of different measures of stød onset (lag from either rime onset, rime midpoint, or vowel midpoint) revealed that lag from rime midpoint minimized variance in stød onset timing across word types. Furthermore, CV:?O/S words had earlier onset/offset times than CVS? words, which had earlier onset times than CV:? words. Together, these results indicate that stød production across different word types is not random but in fact modulated by syllable shape.
Interactions between fundamental frequency and fricative spectral balance in Mandarin Chinese: A corpus study
Authors: Johnson Heather , Barnes Jonathan
Published: December 2020

Voiceless segments create obvious problems for the realization of linguistic tone contours. Niebuhr 2012 hypothesizes that speakers compensate for gaps in F0 using non-F0 cues to support threatened contrasts. For example, in several intonation languages, spectral balance in voiceless fricatives appears to covary in certain contexts with local F0 levels, suggesting that listeners may use raised spectral center-of-gravity (CoG) as a perceptual proxy for high F0 where the latter is absent. To our knowledge, however, this pattern has yet to be identified in a lexical tone language. This study investigates Mandarin Chinese voiceless fricative spectra in contrasting lexical tone contexts, using data from the AISHELL-1 Mandarin Speech Corpus (one talker, 3,562 words). 778 fricatives were located using the Penn Phonetics Forced Aligner for Chinese, and measurements for closure duration, intensity, CoG, and surrounding F0 levels were taken with Praat. Both consonant place and following vowel context exhibited expected effects on fricative CoG. Preceding and following lexical tone categories did not. We did, however, identify a small but significant positive relationship between following F0 levels, and fricative CoG. This is discussed both in terms of compensation for missing F0, and as an indirect consequence of increased intensity under raised F0.
A syntactic-prosodic analysis of focalizing “ser.”
Authors: Flores Tanya , Mendez Vallejo Catalina
Published: December 2020

This project examines the relationship between an innovative syntactic structure in Colombian Spanish and its prosodic description. The focalizing ser (FS) is a dialectally marked syntactic structure in which ser is generated in a clause-internal focus phrase and functions as a discourse link between given and new information (Méndez Vallejo, 2009; Pato, 2010). The following is an example of FS for “It was the puppy who left barking”: Salió ladrando fue el perrito leave-3SG-PAST bark-PROGR be-3SG-PAST the puppy This is the first analysis on how FS is marked prosodically, and how it compares to cleft and pseudo-cleft focus structures. Data were collected from 40 speakers, 10 from each of four Colombian cities: Barranquilla, Bogotá, Cali, and Medellín. Our results show that FS behaves differently from other focus structures in terms of prosodic marking. Unlike ser in cleft and pseudo-cleft structures, ser in FS structures can be prosodically marked with a prenuclear pitch accent. This study reveals that although FS is considered a discourse or emphatic marker (Curnow and Travis, 2004; Pato, 2010), it can behave like a content word in terms of syntax and prosody, even receiving prosodic focus marking.
Prosodic structural and tonal contextual modulation of Voice Onset Time and consonant-induced fundamental frequency in the three-way laryngeal contrast in Thai
Authors: Silpachai Alif
Published: December 2020

Voice Onset Time (VOT) and consonant-induced fundamental frequency (CF0) may signal phonological laryngeal contrasts. This signaling may be modulated by prosodic structure and pitch context. However, such modulation in tonal languages is unclear. This study investigates the roles of prosodic structure and tonal context in the phonetic implementation of laryngeal contrasts in Thai, a tonal language with a three-way laryngeal contrast. Monosyllabic words with /b/, /p/, or /ph/ as the onset, bearing the falling (51), mid (32), or low (21) tone, and produced at the Intonational Phrase (IP) boundary or the Word boundary were analyzed. Results showed modulation of VOT and CF0 by prosodic structure and tonal context across laryngeal contrasts. The VOTs of /b/ and /ph/ at the IP boundary were longercompared to their counterparts at the Word boundary. The CF0s of /b/ and /p/ across all tones were lower at the IP boundary compared to their counterparts at the Word boundary. An observed CF0 effect was more visible with the falling tone compared to the mid tone; no such effect was found with the low tone. Within the falling and mid tones, the CF0 effect occurred more at the IP boundary compared to at the Word boundary.
Phonetic evidence for categorical differences in prosodic structure
Authors: Kim Seung-Eun , Tilsen Sam
Published: December 2020

An experiment was conducted to assess phonetic evidence for categorically distinct prosodic structures associated with two types of relative clauses in English. Non-restrictive relative clauses (NRRCs) and restrictive relative clauses (RRCs) have been argued to be typically produced with different prosodic phrase structures. To test whether there is evidence for this, productions of the two relative clauses were elicited. A wide range of variation in speech rate was elicited by using a moving visual analogue which cued participants for rate variation. Acoustic and articulatory data were collected from twelve participants. We assessed whether the functional relations between speech rate and various phonetic measures at phrase boundaries differed by syntactic context. In addition, linear and sigmoidal models were fit to each of the articulatory and acoustic measures within each syntactic context, and the corrected Akaike Information Criterion (AICc) was used to determine whether the sigmoidal model provides a substantially better fit than the linear model. Although most of the phonetic measures showed a significant difference between the two syntactic structures, which provides some evidence for distinct prosodic categories, the non-linearity analyses in both structures showed weak evidence for categorical variation in prosodic structure.
Explaining neural network predictions of acoustic fields in ideal single- and multi-path environments
Authors: Lee Brandon M. , Dowling David R.
Published: December 2020

Neural networks are an increasingly popular tool for solving a wide variety of problems. Given some up-front computational effort, the complex patterns which exist in large datasets can be embedded in an explicit, though difficult to interpret, neural-network ‘formula’ for future predictions. As reliance on neural networks increases, so does the demand for their explainability, since practitioners must create safe and unbiased methods. In this presentation, an effort is made to better explain and understand neural networks which are trained to provide solutions to the point-source Helmholtz-equation in axisymmetric single-path, two-path, and multi-path (ideal waveguide) environments having constant sound speed. This analysis emphasizes source frequencies in the 100s of Hz, depths up to 500 m, and ranges up to 1 km for sound speeds near 1500 m/s. In all cases, the neural networks' intermediate computational values are compared to those of the corresponding analytical Helmholtz-equation solution used to generate the neural networks' training dataset. The effects of the choice of neural network inputs, noise-like inputs, and correlated input features are also considered. The insights developed from this investigation provide insights for the extension of neural network predictions of acoustic fields to more complex environments. [Work supported by the NDSEG fellowship program.]
Geoacoustic parameter estimation using machine learning techniques
Authors: Potty Gopu R. , Miller James H. , Gopu Vishakh R. , Michalopoulou Zoi-Heleni , Bonnel Julien
Published: December 2020

The Airy phase region corresponding the minimum group velocity of the dispersive acoustic normal modes in shallow water are extremely sensitive to bottom properties. The group speed minima and the associated frequency data for two lower order modes were used to train a neural network to predict the bottom parameters in a previous study (Potty et al., 2019). The geoacoustic model for the bottom consisted of a sediment layer over acoustic basement. Synthetic data generated by varying the values of the sound speeds in the sediment layer and basement were used to train and evaluate the technique. The output of the neural network was used as the background model for a linear perturbation inversion. Data collected from the Shelf break Primer experiment were used to test the algorithm and the preliminary results were promising. This study will continue the previous work by incorporating higher order modes in the training data, testing with data from other experiments and using other machine learning techniques. The performance of this hybrid approach (neural network combined with linearized inversion) will be compared with fully non-linear inversion, both in terms of accuracy and computation time. [Work supported by the Office of Naval Research.]
Active listening and learning for orca sound detection
Authors: Mehta Kunal B. , Rodriguez Saltijeral Jorge , Lopez Jesse , Singh Abhishek , Staneva Valentina , Veirs Scott , Veirs Val
Published: December 2020

Southern Resident Killer Whales are in danger of extinction, however, the current approaches to detect and study their habitat are very time and labor consuming. To streamline this process we have built an active learning system leveraging the vast streams of passive acoustic data collected by hydrophones, the advances in machine learning for audio analysis, and the expertise of trained bioacousticians. The system visualizes predictions of a machine learning algorithm on raw data and allows input from the user to verify and correct them, thus supplementing the existing training dataset and also engaging the user in the annotation process. Researchers can focus on labeling only observations for which the algorithm has high uncertainty, while most of the data get labeled automatically. We show that the active learning system improves the performance of a Convolutional Neural Network algorithm on a two-category classification problem (presence/absence of a call) even with very few extra annotations: the f1-score increased from .83 to .84 with 50 new annotations (∼3% increase of the labeled dataset). We have designed the system flexible to incorporate other algorithms and facilitate result comparison within the community. It is also open source and easy to deploy on diverse computing infrastructures.
Unsupervised clustering of coral reef fish calls
Authors: Reeves Ozanich Emma , Thode Aaron M. , Gerstoft Peter , Freeman Simon E. , Freeman Lauren A.
Published: December 2020

An unsupervised process is proposed for clustering and identifying fish calls in an acoustically active coral reef soundscape. First, potentially localizable acoustic events were detected on three directional autonomous seafloor acoustic recorders (DASARs), sampled at 1 kHz, using an automatic directional detector. A maximum likelihood localization algorithm was used to remove unlocalizable events. For each localizable event, standard acoustic metrics were extracted from the spectrogram and timeseries, while user-agnostic latent features were extracted from the spectrograms by an undercomplete convolutional autoencoder (CAE) neural network. Unsupervised clustering methods, including K-means and agglomerative hierarchical, identified distinct acoustic classes from both feature sets. The unsupervised clustering process was used to analyze data collected near a Hawaiian coral reef in February 2020. During a 24-h period, about 1 event per second was detected, with diel variation in the number of detected events. Compared to a hand labeled test set, the unsupervised clustering process with standard acoustic metrics was 91% accurate at identifying fish call trains, which were associated with dusk chorusing, as opposed to single pulse calls or Humpback whale sound. The tradeoffs between physical features and CAE latent features for unsupervised call discovery are discussed.
Seabed classification using localized forward modeling and deep learning
Authors: Frederick Christina , Villar Soledad , Michalopoulou Zoi-Heleni
Published: December 2020

We use full wave solutions to generate synthetic high-frequency data for training seafloor classifiers with acoustic signals in the ocean. We expect to recover high level details that cannot be achieved by standard forward models that do not include seafloor roughness. By creating acoustic templates using micro local analysis of full-wave simulations on smaller domains, we avoid the high cost of solving the equations on large domains, the main obstacle in full wave inversion. To demonstrate the usefulness of this modeling, we generate a training library of templates and show how well these can be used in classifying seafloor parameters. We consider two-layer seafloors with varying material types and thicknesses. We address the geoacoustic inversion problem with standard machine learning techniques and more sophisticated deep learning methods. The standard classifiers provide results with worse accuracy that do not generalize well to other test environments; the deep learning classifiers are more costly to train but have higher accuracy, generalizing better. We compare the performance with simulations performed at lower frequencies using a normal mode approach with no roughness effects, where the classification problem becomes simpler. [Work supported by NSF, EOARD, and ONR.]
A non-convex regularization based line artefact quantification method in lung ultrasound imagery for pulmonary disease evaluation
Authors: Karakus Oktay , Anantrasirichai Nantheera , Basarab Adrian , Achim Alin
Published: December 2020

Lung (Pulmonary) diseases are among the most severe health problems which cause multiple deaths (more than 100 thousand people in the UK) every year. Moreover, following the COVID-19 pandemic, analysis and diagnosis of pulmonary disease became even more crucial. The common feature in all clinical conditions, both local to the lungs [e.g., pneumonia, chronic obstructive pulmonary disease (COPD)] and those manifesting themselves in the lungs (e.g., kidney disease, COVID-19) is the presence in lung ultrasound (LUS) images of a variety of artefacts. This work presents a novel method for line artefacts quantification in LUS images of pulmonary disease patients by using a non-convex regularization method. We employ a simple local maxima detection technique in the Radon transform domain, associated with known clinical definitions of line artefacts. Notwithstanding its non-convex characteristics, the proposed technique is guaranteed to converge through our proposed Cauchy proximal splitting (CPS) method and accurately identifies both horizontal (pleural, sub-pleural, A-) and vertical (B- and Z-) line artefacts in LUS images. The proposed method includes a two-stage validation mechanism, which is performed in both Radon and image domains to reduce the number of false and missed detections.
Assessment of COVID-19 in lung ultrasound by combining anatomy and sonographic artifacts using deep learning
Authors: Bagon Shai , Galun Meirav , Frank Oz , Schipper Nir , Vaturi Mordehay , Zalcberg Gad , Soldati Gino , Smargiassi Andrea , Inchingolo Riccardo , Torri Elena , Perrone Tiziano , Mento Federico , Demi Libertario , Eldar Yonina
Published: December 2020

When assessing severity of COVID19 from lung ultrasound (LUS) frames, both anatomical phenomena (e.g., the pleural line, presence of consolidations), as well as sonographic artifacts, such as A-lines and B-lines are of importance. While ultrasound devices aim to provide an accurate visualization of the anatomy, the orientation of the sonographic artifacts differ between probe types. This difference poses a challenge in designing a unified deep artificial neural network capable of handling all probe types. In this work we improve upon Roy et al. (2020): We train a simple deep neural network to assess the severity of COVID-19 from LUS data. To address the challenge of handling both linear and convex probes in a unified manner we employed two strategies: First, we augment the input frames of convex probes with a “rectified” version in which A-lines and B-lines assume a horizontal/vertical aspect close to that achieved with linear probes. Second, we explicitly inform the network on the presence of important anatomical features and artifacts. We use a known Radon-based method for detecting the pleural line and B-lines and feed the detected lines as inputs to the network. Preliminary experiments yielded f1 = 68.7% compared to f1 = 65.1% reported by Roy et al.
Modeling infrasound propagation from Tornado producing storms
Authors: Wilson Trevor C. , KC Real J. , Elbing Brian R. , Van Den Broeke Matthew S.
Published: December 2020

Tornado producing storms have been shown to emit infrasound (sound below 20 Hz) before and after tornadogenesis. This infrasound can be detected over large distances due to the low atmospheric attenuation of sound signals at low frequencies. The ability for infrasound signals to travel large distances could allow for the use of infrasound microphone arrays to assist with tornado detection and improve tornado warnings. The current work will focus on investigating the effects of the local atmosphere on a propagating infrasound signal by running simulations utilizing an atmospheric modeling code known as AVO-G2S and a collection of numerical models for the propagation of infrasound known as NCPAprop. This work will report the results from these simulations which investigated tornado and hail producing storms that occurred in Oklahoma between 2017 and 2020. Particularly, the impact of acoustic and atmospheric models on emitted infrasound signals will be investigated. [This work was funded by NOAA under Grant No. NA19OAR4590340.]
Holistic, long-term soundscape monitoring in Upstate New York using convolutional long short-term memory deep neural networks
Authors: Morgan Mallory , Braasch Jonas
Published: December 2020

As part of a long-term bioacoustics monitoring project, audio data containing both anthrophony and biophony was collected 24/7 in a residential area of upstate NY for ten months of the 2019–2020 year. To analyze the ecological content of the data with as little manual intervention as possible, the data is automatically classified using deep learning techniques. First, the data is segmented and fed through a binary CNN long short-term memory network to separate “signal” from “silence.” Next, a small subset of the dataset is manually annotated via visual inspection of log-mel spectrograms to train a multiclass CNN-LSTM—a method which reaches testing accuracies of over 90%. Algorithm performance on this manually annotated dataset is compared to performance on unabridged, “real world” audio data, and strategies to handle issues such as lack of training data, multi-label classification, and the “none of the above” class are also explored. The classification results are ultimately used to generate long-term seasonal sound maps which are cross-referenced with local weather data.
Characterizing the acoustic impedance and attenuation of biocompatible elastomers: An optimal design of experiments approach
Authors: Rennoll Valerie , McLane Ian M. , Elhilali Mounya , West James
Published: December 2020

Polymers have a range of densities and stiffnesses that can be further tuned with the addition of dopants to control their acoustic impedance and attenuation, important properties that impact acoustic transduction in underwater, medical, and other non-airborne applications. Previous research on impedance-matched polymers is limited in scope, focusing on a specific application and varying a limited number of variables independently. Here, we perform a more generalized study to model the relationship between multiple fabrication and characterization conditions on the acoustic impedance and attenuation of biocompatible elastomers with ceramic nanoparticle dopants. Following an I-optimal design of experiments approach, fifty samples were characterized with factors of polymer type (PDMS, Ecoflex, and Polyurethane), sample thickness, dopant density, concentration, and size, and characterization frequency and temperature. Statistical analysis revealed the main variables, as well as interactions between variables, that have a significant affect on the acoustic properties of the elastomers. The resulting statistical model specifies the conditions necessary to match the polymers to any acoustic impedance in the range of 1 to 2.5 MRayls. We demonstrate how the model is used to fabricate an elastomer with an acoustic impedance matched to skin and minimum attenuation.
Graduate programs at the University of Minnesota related to acoustics
Authors: Whiteford Kelly L. , Nelson Peggy , Lim Hubert H. , Bee Mark A. , Oxenham Andrew J.
Published: December 2020

The University of Minnesota (UMN) has graduate programs that span the areas of Animal Bioacoustics, Psychological and Physiological Acoustics, and Speech Communication. Degrees are offered in Psychology (Ph.D.), Speech-Language-Hearing Sciences (M.A. in speech-language pathology, Au.D., and Ph.D. in speech-language-hearing sciences), Biomedical Engineering (M.S. and Ph.D.), Ecology, Evolution, and Behavior (Ph.D.), and Neuroscience (Ph.D.). Faculty across departments have a shared interest in understanding how the ear and brain work together to process sound and in developing new technologies and approaches for improving hearing disorders. Located on campus is the Center for Applied and Translational Sensory Science (CATSS), which provides opportunities for interdisciplinary collaborations across departments and industry to understand how sensory impairments work. Within CATSS is the Multi-Sensory Perception Lab, which houses shared equipment, including eye trackers and electroencephalography. The NSF-funded Graduate Training Program in Sensory Science offers support to graduate students through opportunities related to research, professional development, and public outreach. The Center for Magnetic Resonance Research houses several ultrahigh field magnets, while the Center for Neural Engineering and affiliated faculty labs also house multiple neuromodulation and neurorecording devices to interact with and monitor neural activity in humans and animals.
Graduate acoustics program at Brigham Young University
Authors: Anderson Brian E. , Neilsen Tracianne B. , Sommerfeldt Scott D. , Gee Kent L. , Blotter Jonathan D. , Thomson Scott L.
Published: December 2020

Graduate studies in acoustics at Brigham Young University prepare students for industry, research, and academia by complementing in-depth coursework with publishable research. Graduate-level coursework provides students with a solid foundation in core acoustics principles and practices and measurement skills, including a strong foundation in experimental techniques and writing technical memoranda. Labs across the curriculum cover calibration, directivity, scattering, absorption, laser Doppler vibrometry, lumped-element mechanical systems, equivalent circuit modeling, arrays, filters, room acoustics, active noise control, and near-field acoustical holography. Recent thesis and dissertation topics include active noise control, directivity of acoustic sources, room acoustics, radiation and directivity of musical instruments, energy-based acoustics, time reversal, nondestructive evaluation, flow-based acoustics, voice production, aeroacoustics, sound propagation modeling, nonlinear propagation, high-amplitude noise analyses, machine and deep learning applied to ambient noise level prediction, crowd noise interpretation, underwater acoustic source localization, and ocean environment classification. The graduate students are expected to present research at professional meetings and publish in peer-reviewed acoustics journals. Graduate students often serve as peer mentors to undergraduate students on related projects and may participate in field experiments to gain additional experience. For updates, follow us @BYUAcoustics
Graduate research opportunities in acoustics at the University of Michigan, Ann Arbor
Authors: Kim Jane H. , Dowling David R.
Published: December 2020

The University of Michigan (UM) is host to a wide array of acoustics research which encompasses many of the Technical Committees of the ASA. Within the Department of Mechanical Engineering alone, work is being done to develop better remote sensing techniques for underwater environments, to better understand the mechanics of the human cochlea, and to build metamaterials allowing for new and exotic acoustic behaviors. Within the UM Medical School, faculty and graduate students are constantly advancing techniques for diagnostic and therapeutic ultrasound procedures. In the Department of Naval Architecture and Marine Engineering, computational and experimental tools are being developed to enable better ship design. And researchers in the Linguistics Department are using the fundamental acoustic processes of speech to learn how humans effectively communicate. And while these are only a sample of the projects taking place at Michigan, new opportunities for acoustics research and collaboration open up each semester. Combined with a rich course catalogue, first-rate facilities, and great prospects for publication, these opportunities prepare UM graduate students for careers in industry and academia alike. Go Blue!
Graduate training opportunities in the hearing sciences at the University of Louisville
Authors: Morgan Shae D. , Stilp Christian , Zahorik Pavel
Published: December 2020

The University of Louisville currently offers two branches of training opportunities for students interested in pursuing graduate training in the hearing sciences: A Ph.D. degree in experimental psychology with concentration in hearing science, and a clinical doctorate in audiology (Au.D.). The Ph.D. degree program offers mentored research training in areas such as psychoacoustics, speech perception, spatial hearing, and multisensory perception, and guarantees students four years of funding (tuition plus stipend). The Au.D. program is a 4-year program designed to provide students with the academic and clinical background necessary to enter audiologic practice. Both programs are affiliated with the Heuser Hearing Institute, which, along with the University of Louisville, provides laboratory facilities and clinical populations for both research and training. An accelerated Au.D./Ph.D. training program that integrates key components of both programs for training of students interested in clinically based research is under development. Additional information is available at: http://louisville.edu/medicine/degrees/audiology and http://louisville.edu/psychology/graduate/vision-hearing.
Directivity of the half-dome bundengan musical instrument
Authors: Kusumaningtyas Indraswari , Christianto Raymond , Parikesit Gea O.
Published: December 2020

Bundengan is a traditional musical instrument from Indonesia that has a half-dome structure. It is fitted with clipped strings and long, thin bamboo bars that generate metal-like and drum-like sounds, respectively. In the past, a bundengan would be played for the personal pleasure of its player. Driven by the needs of conservation, nowadays, its use is steered towards stage performance for a larger audience. In this work, we investigate the directivity of the bundengan as one of the important aspects to consider when setting the musical instrument on stage. We measured the sound of plucked strings from four bundengans, made by traditional and contemporary craftsmen. The sound was recorded at a radius of 1 m from the centerline of the base of the instruments and at a height of 0.5 m from the floor, covering a circular angle of 360 deg. The bundengans generally produce comparable directivity patterns. Still, a number of differences are observed, possibly due to the small variations in the size of the domes and the placements of the strings inside the domes. These directivity plots provide the possibility to assess how suitable the bundengan actually is for stage performance. [Work supported by the National Geographic Society.]
A suggested modification to ANSI S12.51 (ISO 3741) Annex D
Authors: Lilly Jerry G.
Published: December 2020

Annex D of ANSI S12.51 (ISO 3741) addresses the issue of qualifying reverberation rooms for determining sound power of fixed sources that emit sound at discrete frequencies. At low frequencies reverberation rooms have reduced modal density which causes a highly varying (spatially) sound field, resulting in a less accurate measure of the space-average sound pressure level in the reverberant field of the room compared to higher frequency bands. Annex D sets limits on the maximum allowable standard deviation in the 1/3-octave bands from 100 Hz to 2,500 Hz, and Annex E provides limits for 50 Hz, 63 Hz, and 80 Hz. This presentation discusses the required test procedure and presents examples of real room qualification test results and how rooms can be modified to meet this requirement. One fairly unique example will also be shown where the room fails to meet the qualification limits, when in fact it truly should. A recommended modification to the data analysis process is suggest to resolve this unique problem.
Subjective quantification of music instrument practice disturbances: A machine audition based approach
Authors: Wu Kevin , Ren Gang , Ogihara Mitsunori
Published: December 2020

Music instrument practice usually causes disturbance to neighbors, especially at tight living spaces with common walls or building structural transmissions. However, the severity of disturbance is difficult to quantify because of the varieties of musical sound, music content, and many subjective factors. We present three studies on the quantification of such disturbances using machine audition tools. In the first study, musical sound at a music practice room and an adjacent room is recorded and analyzed for quantifying the disturbance caused to adjacent rooms. This study builds a quantification framework for disturbance by applying musical pattern recognition tools such as pitch tracking and onset detection to imitate humans' musical perceptions. The machine audition results are correlated with subjective rating results for calibrating the disturbance scales. The second study explores the frequency-selective transmission profiles and ambient noise patterns and their correlations to machine-rated disturbance levels and subjectively rated disturbance levels. The third study explores the effect of acoustical environment on musicians. A professional musician can adapt to the acoustical environment by making adjustments to the performance he has prepared for and these adjustments form a feedback loop that affects both the practice experience and the perceived disturbance level.