Analysis Of Acoustic Data Research Articles

Automated detection of sigmatism using deep learning applied to multichannel speech signal

This paper presents a system for the analysis of acoustic data for the computer-aided diagnosis and therapy of sigmatism in children. The analysis is focused on the detection and recognition of selected articulation disorders in sibilant sounds. The system relies on the dedicated data acquisition device recording the speech signal using 15 microphones spatially arranged around the speaker's mouth. The collected speech corpus contains 923 samples of the /s/ and /ʃ/ consonants from 98 five- and six-year-old children with either normative or pathological pronunciation features. Each recording is supplemented with a detailed speech therapy annotation. A dedicated multibranch convolutional neural network architecture was designed for the speech sample classification. The filter bank energy feature maps are extracted from each channel along with their two derivatives in the time domain. The feature maps are aggregated along different dimensions to constitute a four-dimensional data structure called acoustic volume, being the input data for the deep network. We proposed three ways to aggregate the multichannel data into the acoustic volume and two techniques for the data augmentation to enlarge the available dataset and avoid overfitting. Classification experiments involving different data subsets have proven the system's ability to detect the analyzed pronunciation disorders with reasonable accuracy. The framework with speech data organized spatially in five channels provides the most efficient classification.

The effect of the extended bridge on the Timbre of the Sarasvati Veena: a numerical and experimental study

An attempt is made to establish the dependence of the timbre of the Sarasvati veena, a South Indian string instrument, on its extended bridge. The equation of motion for a plucked string vibrating against the extended boundary at the bridge is solved numerically. The solution is analyzed for timbre characteristics, which show energy redistribution among the higher harmonics, as well as revival of higher harmonics with time. The variation of timbre with bridge slope and curvature are analyzed. These results are validated by comparison with corresponding analysis of acoustic data gathered from experiments performed on a sonometer, whose knife edge is replaced by the bridge of the veena.

Dynamics of currents and biological scattering layers around Senghor Seamount, a shallow seamount inside a tropical Northeast Atlantic eddy corridor

Biophysical interactions of the mesopelagic fauna and hydrodynamic features were investigated at a shallow, tall seamount in the tropical Northeast Atlantic based on data from three inter-disciplinary surveys collected between 2009 and 2015. Senghor Seamount is located close to the equator in a unique but underexplored oceanographic setting, where classical seamount effects are expected to be small. Shipboard Acoustic Doppler Current Profiler (ADCP) and remote sensing data revealed flow phenomena strongly varying over different temporal and spatial scales. The quasi-steady, longer period flow at the seamount was largely unchanged by flow-topography interaction with the exception of a persistent and recurring shadow zone of weaker currents downstream of the summit. Senghor Seamount is exposed to energetic mesoscale eddy activity in surrounding waters with potentially large physical and biological implications. At higher frequencies, tidal currents interacting with the seamount generated large-amplitude internal waves propagating horizontally and vertically away from the summit. Analysis of acoustic backscatter data and micronekton biomass displayed prominent near-surface night time and deep (>400 m) day time scattering layers associated with the diurnal vertical migration of the mesopelagic fauna. An intense and previously unreported aggregation of acoustic scatterers was detected in the depth range 150–300 m inside a radius of 3 km along the upper slopes of the seamount summit. ADCP measurements over a full semi-diurnal tidal cycle suggest that biophysical interactions were present in near-seafloor waters around the upper seamount as evidenced by plankton distributions that were modified by topographic blocking during descent and aggregation in waters characterised by internal waves and enhanced tidally-driven energy dissipation.

Comparative bioacoustics: a roadmap for quantifying and comparing animal sounds across diverse taxa.

Animals produce a wide array of sounds with highly variable acoustic structures. It is possible to understand the causes and consequences of this variation across taxa with phylogenetic comparative analyses. Acoustic and evolutionary analyses are rapidly increasing in sophistication such that choosing appropriate acoustic and evolutionary approaches is increasingly difficult. However, the correct choice of analysis can have profound effects on output and evolutionary inferences. Here, we identify and address some of the challenges for this growing field by providing a roadmap for quantifying and comparing sound in a phylogenetic context for researchers with a broad range of scientific backgrounds. Sound, as a continuous, multidimensional trait can be particularly challenging to measure because it can be hard to identify variables that can be compared across taxa and it is also no small feat to process and analyse the resulting high-dimensional acoustic data using approaches that are appropriate for subsequent evolutionary analysis. Additionally, terminological inconsistencies and the role of learning in the development of acoustic traits need to be considered. Phylogenetic comparative analyses also have their own sets of caveats to consider. We provide a set of recommendations for delimiting acoustic signals into discrete, comparable acoustic units. We also present a three-stage workflow for extracting relevant acoustic data, including options for multivariate analyses and dimensionality reduction that is compatible with phylogenetic comparative analysis. We then summarize available phylogenetic comparative approaches and how they have been used in comparative bioacoustics, and address the limitations of comparative analyses with behavioural data. Lastly, we recommend how to apply these methods to acoustic data across a range of study systems. In this way, we provide an integrated framework to aid in quantitative analysis of cross-taxa variation in animal sounds for comparative phylogenetic analysis. In addition, we advocate the standardization of acoustic terminology across disciplines and taxa, adoption of automated methods for acoustic feature extraction, and establishment of strong data archival practices for acoustic recordings and data analyses. Combining such practices with our proposed workflow will greatly advance the reproducibility, biological interpretation, and longevity of comparative bioacoustic studies.

The power of national acoustic tracking networks to assess the impacts of human activity on marine organisms during the COVID-19 pandemic

COVID-19 restrictions have led to an unprecedented global hiatus in anthropogenic activities, providing a unique opportunity to assess human impact on biological systems. Here, we describe how a national network of acoustic tracking receivers can be leveraged to assess the effects of human activity on animal movement and space use during such global disruptions. We outline variation in restrictions on human activity across Australian states and describe four mechanisms affecting human interactions with the marine environment: 1) reduction in economy and trade changing shipping traffic; 2) changes in export markets affecting commercial fisheries; 3) alterations in recreational activities; and 4) decline in tourism. We develop a roadmap for the analysis of acoustic tracking data across various scales using Australia's national Integrated Marine Observing System (IMOS) Animal Tracking Facility as a case study. We illustrate the benefit of sustained observing systems and monitoring programs by assessing how a 51-day break in white shark (Carcharodon carcharias) cage-diving tourism due to COVID-19 restrictions affected the behaviour and space use of two resident species. This cessation of tourism activities represents the longest break since cage-diving vessels started day trips in this area in 2007. Long-term monitoring of the local environment reveals that the activity space of yellowtail kingfish (Seriola lalandi) was reduced when cage-diving boats were absent compared to periods following standard tourism operations. However, white shark residency and movements were not affected. Our roadmap is globally applicable and will assist researchers in designing studies to assess how anthropogenic activities can impact animal movement and distributions during regional, short-term through to major, unexpected disruptions like the COVID-19 pandemic.

Deep Learning for Deep Waters: An Expert-in-the-Loop Machine Learning Framework for Marine Sciences

Driven by the unprecedented availability of data, machine learning has become a pervasive and transformative technology across industry and science. Its importance to marine science has been codified as one goal of the UN Ocean Decade. While increasing amounts of, for example, acoustic marine data are collected for research and monitoring purposes, and machine learning methods can achieve automatic processing and analysis of acoustic data, they require large training datasets annotated or labelled by experts. Consequently, addressing the relative scarcity of labelled data is, besides increasing data analysis and processing capacities, one of the main thrust areas. One approach to address label scarcity is the expert-in-the-loop approach which allows analysis of limited and unbalanced data efficiently. Its advantages are demonstrated with our novel deep learning-based expert-in-the-loop framework for automatic detection of turbulent wake signatures in echo sounder data. Using machine learning algorithms, such as the one presented in this study, greatly increases the capacity to analyse large amounts of acoustic data. It would be a first step in realising the full potential of the increasing amount of acoustic data in marine sciences.

Species diversity and biogeography of an ancient frog clade from the Guiana Shield (Anura: Microhylidae:Adelastes,Otophryne,Synapturanus) exhibiting spectacular phenotypic diversification

AbstractThe outstanding biodiversity of the Guiana Shield has raised many questions about its origins and evolution. Frogs of the genera Adelastes, Otophryne and Synapturanus form an ancient lineage distributed mostly across this region. These genera display strikingly disparate morphologies and life-history traits. Notably, Synapturanus is conspicuously adapted to fossoriality and is the only genus within this group to have dispersed further into Amazonia. Moreover, morphological differences among Synapturanus species suggest different degrees of fossoriality that might be linked to their biogeographical history. Through integrative analysis of genetic, morphometric and acoustic data, we delimited 25 species in this clade, representing a fourfold increase. We found that the entire clade started to diversify ~55 Mya and Synapturanus ~30 Mya. Members of this genus probably dispersed three times out of the Guiana Shield both before and after the Pebas system, a wetland ecosystem occupying most of Western Amazonia during the Miocene. Using a three-dimensional osteological dataset, we characterized a high morphological disparity across the three genera. Within Synapturanus, we further characterized distinct phenotypes that emerged concomitantly with dispersals during the Miocene and possibly represent adaptations to different habitats, such as soils with different physical properties.

Interlingual Interactions Elicit Performance Mismatches Not “Compromise” Categories in Early Bilinguals: Evidence from Meta-Analysis and Coronal Stops

Previous studies attest that some early bilinguals produce the sounds of their languages in a manner that is characterized as “compromise” with regard to monolingual speakers. The present study uses meta-analytic techniques and coronal stop data from early bilinguals in order to assess this claim. The goal was to evaluate the cumulative evidence for “compromise” voice-onset time (VOT) in the speech of early bilinguals by providing a comprehensive assessment of the literature and presenting an acoustic analysis of coronal stops from early Spanish–English bilinguals. The studies were coded for linguistic and methodological features, as well as effect sizes, and then analyzed using a cross-classified Bayesian meta-analysis. The pooled effect for “compromise” VOT was negligible (β = −0.13). The acoustic analysis of the coronal stop data showed that the early Spanish–English bilinguals often produced Spanish and English targets with mismatched features from their other language. These performance mismatches presumably occurred as a result of interlingual interactions elicited by the experimental task. Taken together, the results suggest that early bilinguals do not have “compromise” VOT, though their speech involves dynamic phonetic interactions that can surface as performance mismatches during speech production.

Joint Analysis of Resident Complaints, Meteorological, Acoustic, and Ground Motion Data to Establish a Robust Annoyance Evaluation of Wind Turbine Emissions

Joint Analysis of Resident Complaints, Meteorological, Acoustic, and Ground Motion Data to Establish a Robust Annoyance Evaluation of Wind Turbine Emissions

It is not just about birds: what do acoustic indices reveal about a Costa Rican tropical rainforest?

ABSTRACT Acoustic monitoring is used to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from large data sets might be exceedingly time consuming. For this reason, acoustic indices have been proposed as proxies for biodiversity monitoring. Although acoustic indices hold great promise for standardizing acoustic data analysis, the complexity of acoustic conditions requires careful examination of the relationship between an index and the underlying process of interest. We evaluated 11 acoustic indices at two operational levels: (1) acoustic community level (an aggregation of species that produces sound), using birds as an example to assess how well acoustic indices predict bird indices (abundance, richness, evenness and diversity); and (2) soundscape level (the collection of biological, geophysical and anthropogenic sounds from a landscape), using acoustic indices to classify the study sites according to their ecological condition. To study the relationship among these variables, we selected two study sites with different ecological conditions (in terms of vegetation structure and traffic noise) within the Braulio Carrillo National Park (BCNP), Costa Rica. We sampled the soundscape and bird community using 12 sampling points and four visits to each study site from June 2017 to August 2018. We continuously recorded sounds at sunrise and sunset, and for 10 minutes every hour, during two consecutive days per visit. In addition, we performed four bird counts per visit (sunrise and sunset). We performed a correlation analysis between 11 acoustic indices and 4 community bird indices. We analyzed the ability of acoustic indices to predict bird indices. Furthermore, we used acoustic indices to classify the two sites according to their ecological condition. Bird abundance and richness were positively correlated with acoustic evenness indices and negatively correlated with the acoustic diversity index, but the whole set of acoustic indices predicted bird indices weakly. However, the classification of the sites using acoustic indices was conducted with a high average precision of 0.93 (sd = 0.08). Acoustic indices appear to be more promising for evaluating the ecological condition of a site than abundance, richness or diversity of specific animal groups, in this case birds, in tropical rainforests.

ON THE IDENTITY OF TWO Fejervarya FROG (DICROGLOSSIDAE) SPECIES FROM THE ANDAMAN AND NICOBAR ARCHIPELAGO

The taxonomic status of the large-sized Fejervarya frogs of the Andaman and Nicobar Islands was assessed based on integrative analysis of molecular, morphological and acoustic data. Our results identify the population from the Andaman Islands as Fejervarya moodiei, and that from the Nicobar Islands as F. limnocharis. Representative specimens collected during this study are described along with observations on their natural history. The distribution of F. moodiei within the Andaman Islands and F. limnocharis in the Nicobar Islands recorded during this study are mapped, suggesting that these species are fairly widespread.

Actel: Standardised analysis of acoustic telemetry data from animals moving through receiver arrays

Abstract Acoustic telemetry data often contain erroneous detections, which need to be addressed before further analysis. It is important that this process is systematic, standardised and reproducible. The r package actel provides a systematic conditional pipeline to filter and analyse acoustic telemetry data in a reproducible fashion, for animals moving between receiver arrays. actel outputs a standardised report containing the main results and the steps taken by the user, in addition to summary information for each animal and other content such as efficiency estimations for each receiver array. actel improves the reproducibility of the acoustic data filtering and analysis, and simplifies the integration of acoustic data sets originating from different studies (in time and/or in space).

Analysis of Acoustic Emission Data for Bearings subject to Unbalance

Acoustic Emission (AE) is an effective nondestructive method for investigating the behavior of materials under stress. In recent decades, AE applications in structural health monitoring have been extended to other areas such as rotating machineries and cutting tools. This research investigates the application of acoustic emission data for unbalance analysis and detection in rotary systems. The AE parameter of interest in this study is a discrete variable that covers the significance of count, duration and amplitude of AE signals. A statistical model based on Zero-Inflated Poisson (ZIP) regression is proposed to handle over-dispersion and excess zeros of the counting data. The ZIP model indicates that faulty bearings can generate more transient wave in the AE waveform. Control charts can easily detect the faulty bearing using the parameters of the ZIP model. Categorical data analysis based on generalized linear models (GLM) is also presented. The results demonstrate the significance of the couple unbalance.

Technical note: An acoustic method for assessing the respiration rate of free-grazing dairy cattle

The aim of this study was to validate whether acoustic data analysis can be used to assess respiration rate (RR) in dairy cattle under grazing systems. Two validation trials, one with heifers and other with lactating cows, were conducted. The RR derived from acoustic data acquired with an MP3 recorder fitted on the halter was compared to the RR derived from a visual method, counting flank movements. Data were analyzed using correlation test and Willmott's index of agreement (d). There was no significant difference (P>0.05) between RR assessed using the acoustic or visual method, in both heifers and lactating cows. The coefficients of determination (R2) indicated that 92.31% (heifers) and 62.09% (lactating cows) of the variability in the RR derived using the visual assessment method was explained by the RR derived using the acoustic method. The d values were 0.99 (heifers) and 0.98 (lactating cows), which denoted good agreement between the RR derived using the two methods. The acoustic method is non-invasive, allows for the assessment of RR in free-grazing dairy cattle and may replace the current standard of visual counting.

In Situ Process Monitoring for Additive Manufacturing Through Acoustic Techniques

Additive manufacturing (AM) is an emerging field where a complex geometrical model can be made with no requirement of individual parts and assembly production. This advantage provides the capability for fabricating components in a single integrated process. On the contrary, lack of non-destructive testing adoption due to complex geometries of final products, makes this technology less convenient for the production of critical parts with high accuracy. Non-destructive testing through acoustic techniques is one of the most popular methodologies for AM inspection because of its provision to detect defects on the internal structure of the components. The technique has also been used in other types of fabrication processes (machining and welding) for defect monitoring. There are several studies where acoustic data acquisition and analysis have been done to detect cracks and other anomalies. In this paper, the progress of using acoustic techniques for AM process and part quality monitoring has been reviewed, and critical discussion has been made for the potential application of acoustic techniques toward quality inspection and monitoring in AM technology.

Characterizing three shallow-water locations off Goa, India, using passive acoustic data.

In this study, an analysis of the passive acoustic data is carried out for the quantitative characterization of shallow-water acoustic environments from three major estuarine systems of Goa during the months of March and April. The identification of fish sounds was carried out using waveform and peak power spectral densities (PSDs) of the individual fish calls. Fish sound data showed that the toadfish of the Batrachoididae family (Colletteichthys dussumieri species) produced a spectral level 112.27 ± 4.48 dB re 1 μPa2 /Hz at 448.96 ± 40.30 Hz frequency from the mangrove-dominated tidally influenced Mandovi estuary. Similarly, in a coral reef area near Grande Island in the Zuari estuary, Tiger Perch fish from the Terapontidae family (Terapon threaps species) were identified, having spectral levels 106.91 ± 3.08 dB re 1 μPa2 /Hz at 1791.56 ± 106.55 Hz frequency. From the Sal estuary, PSD levels were found to be around 98.24 ± 2.98 dB re 1 μPa2/Hz at 1796.95 ± 72.76 Hz frequency for Tiger Perch of the Terapontidae family (T. threaps species). To characterize the contributions of biophony (fish), geophony (wind and flow, etc.), and anthrophony (boats, etc.), cluster analysis is employed. In the Mandovi estuary, the root-mean-square sound pressure level (SPLrms) of broadband toadfish was a function of the water flow and temperature. In the Zuari estuary, SPLrms was a function of the water temperature and wind, whereas in the Sal estuary, wind mainly influenced the SPLrms.

Pore type identification in carbonate rocks using convolutional neural network based on acoustic logging data

Existing methods of well logging interpretation often contain uncertainties in the exploration and evaluation of carbonate reservoirs due to the complex pore types. Based on the time–frequency analysis of array acoustic logging data, the identification of pore types based on a convolutional neural network (CNN) was established. The continuous wavelet transform was first used to transform the 1-D acoustic wave data into 2-D time–frequency spectra as the input data of the CNN based on the pore aspect ratios. According to the acoustic logging data obtained from numerical simulations, a three-type (vug, interparticle-pores, and crack) prediction was established to validate the identification method. The noise-sensitivity analyses demonstrate that our method is stable for noise mixed signals. The CNN-based identification method was used to analyze the field acoustic logging data in a carbonate reservoir. According to the description of the pore structures from the core analysis, the formation pores were divided into two types (cracks and interparticle-pores). The accuracy of the method using field acoustic logging data can reach 90%. This work provides promising means for pore type identification from complex acoustic logging data by applying deep learning technologies, which can be easily extended into other similar neighboring carbonate reservoirs.

Seasonal trends and primary contributors to the low-frequency soundscape of the Cordell Bank National Marine Sanctuary

Passive acoustic monitoring of ocean soundscapes can provide information on ecosystem status for those tasked with protecting marine resources. In 2015, the National Oceanic and Atmospheric Administration (NOAA) established a long-term, continuous, low-frequency (10 Hz-2 kHz) passive acoustic monitoring site in the Cordell Bank National Marine Sanctuary (CBNMS), located offshore of the central United States of America (U.S.) west coast, near San Francisco, CA. The California Current flows southward along the coast in this area, supporting a diverse community of marine animals, including several baleen whale species. Acoustic data analysis revealed that both large vessels and vocalizing baleen whales contribute to the ambient soundscape of the CBNMS. Sound levels fluctuated by month with the highest levels in the fall and lowest levels in the summer. Throughout the year, very low-frequency (10-100 Hz) sound levels were most variable. Vessels and whales overlap in their contributions to ambient sound levels within this range, although vessel contributions were more omnipresent, while seasonal peaks were associated with vocalizing whales. This characterization of low-frequency ambient sound levels in the CBNMS establishes initial baselines for an important component of this site's underwater soundscape. Standardized monitoring of soundscapes directly supports NOAA's ability to evaluate and report on conditions within national marine sanctuaries.

A new soundscape analysis tool: Soundscape Analysis and Mapping System (SAMS)

There is currently considerable interest in the quantitative analysis tools of soundscape to derive supplemental information of a landscape. However, existing soundscape software for acoustic data analyses does not consider the geospatial characteristics of the landscape although they are essential components of soundscape ecology. The new software described in this paper, Soundscape Analysis and Mapping System (SAMS), allows users to quickly process and analyze large volumes of acoustic data in geospatial environment. Specifically, SAMS integrates soundscape data with landscape information and visualization on the same platform that can be directly retrieved from Google Earth. A soundscape case study, used as an example to demonstrate usefulness of the SAMS tool, revealed an obvious spatial heterogeneity of soundscape across the landscape. Further analyses suggested that the transformation of natural wetland ecosystems into various dispersed urban structures directly led to significant changes in soundscape properties, implying human-noise intrusion and reduction in avian vocalizations. Therefore, this new SAMS software offers a novel analytical tool for users, such as urban planners or acoustic ecologists, to assess the impact of spatial patterns on soundscape characteristics.

The inconspicuous substratum

AbstractDescriptions of Australian Aboriginal English list the neutralisation of the Standard English contrast between so-called voiced and voiceless stops as one characteristic feature. This paper reports on the results of an acoustic analysis of data collected in a production task by monolingual speakers of Standard Australian English in Sydney, of Aboriginal English on Croker Island, Northern Territory, and bilingual speakers of Iwaidja/Aboriginal English and Kunwinjku/Aboriginal English on Croker Island. The results show that average values for Voice Onset Time, the main correlate of the “stop voicing contrast” in English, and Closure Duration collected from Aboriginal speakers of English do not significantly differ from that of speakers of Standard Australian English, irrespective of language background. This result proves that the stop contrast is not neutralised by these Aboriginal speakers of English. However, it can be shown that phonetic voicing manifesting itself in Voice Termination Time is a prevalent and characteristic feature of Aboriginal English on Croker Island. This feature aligns Aboriginal English on Croker Island with local Aboriginal languages and differentiates it from Standard Australian English.