01193nas a2200157 4500008004100000020001500041245002600056210002200082520079100104100001900895700001800914700001800932700001500950700001900965856005100984 2002 eng d a158113454100aThe sound of one hand0 asound of one hand3 a

Two hundred and fifty years ago the Japanese Zen master Hakuin asked the question, "What is the Sound of the Single Hand?" This koan has long served as an aid to meditation but it also describes our new interaction techinique. We discovered that gentle fingertip gestures such as tapping, rubbing, and flicking make quiet sounds that travel by bone conduction throughout the hand. A small wristband-mounted contact microphone can reliably and inexpensively sense these sounds. We harnessed this "sound in the hand" phenomenon to build a wristband-mounted bio-acoustic fingertip gesture interface. The bio-acoustic interface recognizes some common gestures that state-of-the-art glove and image-processing techniques capture but in a smaller, mobile package.

1 aTerveen, Loren1 aWixon, Dennis1 aAmento, Brian1 aHill, Will1 aTerveen, Loren uhttp://portal.acm.org/citation.cfm?doid=50644301722nas a2200145 4500008004100000245011600041210006900157520113200226100001801358700002601376700002201402700002001424700001401444856011801458 2019 eng d00aSocial Network Analysis of an Acoustic Environment: The Use of Visualised Data to Characterise Natural Habitats0 aSocial Network Analysis of an Acoustic Environment The Use of Vi3 a

(1) Background: Ecologists use acoustic recordings for long term environmental monitoring. However, as audio recordings are opaque, obtaining meaningful information from them is a challenging task. Calculating summary indices from recordings is one way to reduce the size of audio data, but the amount of information of summary indices is still too big. (2) Method: In this study we explore the application of social network analysis to visually and quantitatively model acoustic changes. To achieve our aim, we clustered summary indices using two algorithms, and the results were used to generate network maps. (3) Results and Discussion: The network maps allowed us to visually perceive acoustic changes in a day and to visually compare one day to another. To enable quantitative comparison, we also calculated summary values from the social network maps, including Gini coefficient (an economical concept adopted to estimate how unevenly the occurrences are distributed). (4) Conclusion: Social network maps and summary values provide insight into acoustic changes within an environment visually and quantitatively.

1 aWang, Junling1 aSankupellay, Mangalam1 aKonovalov, Dmitry1 aTowsey, Michael1 aRoe, Paul uhttps://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8943071https://ieeexplore.ieee.org/document/8945963/01890nas a2200145 4500008004100000245010000041210006900141260005100210520134100261100002001602700002601622700002101648700002001669856005501689 2016 eng d00aAssessing the effect of aquatic noise on fish behavior and physiology: a meta-analysis approach0 aAssessing the effect of aquatic noise on fish behavior and physi aDublin, IrelandbAcoustical Society of America3 a

Due to the extreme distance that sounds can travel through water, many marine species rely on the soundscape for auditory information regarding predator or prey locations, communication, and habitat selection. These species not only take advantage of the prevailing sounds but also contribute to the soundscape through their own vocalizations. Certain sounds have been shown to have negative effects on marine species, resulting in disrupted communication and unbalanced predator-prey interactions. Unfortunately, the vast majority of soundscape studies are biased towards marine mammals, and only recently has attention been directed towards the potential repercussions for fishes. In an attempt to determine the implications that changes to the soundscape may have on the fishes, a meta-analysis was conducted focusing primarily on the role that anthropogenic noises may play in altering fish behavior and physiology. The review identified 3,174 potentially relevant papers of which were 27 used. The analysis indicates that anthropogenic noise has an adverse effect on marine and freshwater fish behavior and physiology. These findings suggest that although certain species may be more susceptible to anthropogenic noise than others, the vast majority of fish have the potential to be negatively affected by noise pollution.

1 aCox, Kieran, D.1 aBrennan, Lawrence, P.1 aDudas, Sarah, E.1 aJuanes, Francis uhttp://asa.scitation.org/doi/abs/10.1121/2.000029101615nas a2200145 4500008004100000245005200041210005200093260001900145520117200164100002001336700002801356700002501384700001901409856004101428 2012 eng d00aSound reception and radiation in a small insect0 aSound reception and radiation in a small insect aNantes, France3 a

Insects are small; this is a fact of their life. In some contexts this is an advantage, such as insects do not injure themselves through the effects of gravity. In other contexts this is a disadvantage, especially in the context of sound production and reception. The wavelengths of sound that insects such as crickets produce and receive are several times larger than their body size. For sound production, this is particularly challenging and inefficient, as sub-wavelength radiation (size to lambda ratio > 1:100) requires great energy expenditure to produce sufficient sound pressure. In receiving sound, they face the reciprocal problem and are inefficient receivers. In addition,  because of their size they cannot rely on cues other animals use to detect the direction of sound. Nonetheless, sound is extremely important to these insects as they use it for mate attraction and to evade predators. We investigate this problem by combining the technique of microscanning laser Doppler vibrometry with finite element modelling; and explain some of the biomechanical tricks a tiny tree cricket uses to overcome the disadvantages of size.

1 aMhatre, Natasha1 aMontealegre-Z, Fernando1 aBalakrishnan, Rohini1 aRobert, Daniel uhttps://bio.acousti.ca/ja/node/5799102311nas a2200181 4500008004100000245006200041210006200103520174300165653002101908653001301929653001901942100002101961700003201982700001902014700002102033700002002054856005502074 2011 eng d00aSound Transduction in the Auditory System of Bushcrickets0 aSound Transduction in the Auditory System of Bushcrickets3 a

Place based frequency representation, called tonotopy,is a typical property of hearing organs for the discrimination of different frequencies. Due to its coiled structure and secure housing, it is difficult access the mammalian cochlea. Hence, our knowledge about in vivo inner-ear mechanics is restricted to small regions. In this study, we present in vivo measurements that focus on the easily accessible, uncoiled auditory organs in bushcrickets, which are located in their foreleg tibiae. Sound enters the body via an opening at the lateral side of the thorax and passes through a horn-shaped acoustic trachea before reaching the high frequency hearing organ called crista acustica. In addition to the acoustic trachea as structure that transmits incoming sound towards the hearing organ, bushcrickets also possess two tympana, specialized plate-like structures, on the anterior and posterior side of each tibia. They provide a secondary path of excitation for the sensory receptors at low frequencies. We investigated the mechanics of the crista acustica in the tropical bushcricket Mecopoda elongata. The frequency-dependent motion of the crista acustica was captured using a laser-Doppler-vibrometer system. Using pure tone stimulation of the crista acustica, we could elicit traveling waves along the length of the hearing organ that move from the distal high frequency to the proximal low frequency region. In addition, distinct maxima in the velocity response of the crista acustica could be measured at ̃7 and ̃17 kHz. The travelling-wave-based tonotopy provides the basis for mechanical frequency discrimination along the crista acustica and opens up new possibility to investigate traveling wave mechanics in vivo.

10aLDV-measurements10atonotopy10atraveling wave1 aNowotny, Manuela1 aUdayashankar, Arun, Palghat1 aWeber, Melanie1 aHummel, Jennifer1 aKössl, Manfred uhttp://aip.scitation.org/doi/abs/10.1063/1.365813102593nas a2200253 4500008004100000245011100041210006900152520185000221653001102071653001802082653001402100653002502114100001802139700001402157700001302171700001402184700001502198700001902213700001602232700001802248700001502266700001702281856004102298 2019 eng d00aField testing and performance evaluation of the Long-term Acoustic Real-Time Sensor for Polar Areas (LARA)0 aField testing and performance evaluation of the Longterm Acousti3 a

In the Arctic, in-situ measurement of the upper water column properties (e.g., salinity and temperature) has been a challenge because of the seasonal sea ice coverage. A Long-term Acoustic Real-Time Sensor for Polar Areas (LARA) was developed, field-tested in the shallow water off Oregon and its performance evaluated. The LARA utilizes a commercially available underwater profiler winch from NiGK, conductivity-temperature-depth (CTD) sensors, and a passive acoustic monitoring (PAM) systems. The sensor section consists of two modules: 1) a satellite antenna with a temperature and depth sensor (TD) and 2) a sensor buoy with a controller, a CTD, and a PAM. Using the two vertically separated temperature and pressure sensors, it is capable of detecting the presence of sea ice by sensing the oceanographic conditions in the upper water column. In addition, using the acoustic sensors, (1) surface wind speed can be estimated from the ambient noise level and (2) enable monitoring of marine mammal calling activity. The winch can be fully controllable from the sensor buoy by acoustic commands. It is capable of aborting an ascent in case sea ice coverage or a high sea state was detected. Although the sea ice detection algorithm could not be tested in Oregon waters, the LARA successfully repeated 94 profiles and transmitted CTD and acoustic detections data via satellite. The wind speed estimates by the PAM were in good agreement with the nearby buoy data. The PAM recorded various biological signals from 10 Hz to 60 kHz including vocalizations of fin, humpback, sperm whales and calls of Pacific white-sided dolphins. The system is capable of repeating 365 profiles or one profile per day for 1 year making it suitable for collecting high-resolution water column data in the extreme weather and water conditions of the Arctic.

10aarctic10abio-acoustics10aprofiling10areal-time detections1 aMatsumoto, H.1 aHaxel, J.1 aKahn, B.1 aRoche, L.1 aTurpin, A.1 aKlinck, Holger1 aDziak, R.P.1 aChildress, J.1 aSexton, K.1 aNakamura, T. uhttps://bio.acousti.ca/ja/node/5791501390nas a2200241 4500008004100000020002200041245006600063210006600129260004400195520060300239653003700842653002200879653002400901653002100925100002100946700001600967700002300983700001801006700002101024700002701045700002101072856005501093 2019 eng d a978-3-030-31634-100aAutomatic Segmentation of Ultrasonic Vocalizations in Rodents0 aAutomatic Segmentation of Ultrasonic Vocalizations in Rodents aChambSpringer International Publishing3 a

Ultrasonic vocalizations studies in rodents have increasingly drawn researchers attention as it have been considered a powerful tool to understand the animals behavior and their interactions in different social and environmental contexts.

This paper presents an entropy-based algorithm for accurate and robust segmentation of mouse ultrasonic calls. Instead of using the conventional energy-based features, the spectral entropy is developed to identify the audio segments accurately. The new approach for mice calls detection has been able to detect up to 97% of the vocalizations.

10aRodents ultrasonic vocalizations10aSignal processing10aSignal segmentation10aSpectral Entropy1 aHenriques, Jorge1 aNeves, Nuno1 ade Carvalho, Paulo1 aPessoa, Diogo1 aPetrella, Lorena1 aCastelo-Branco, Miguel1 aTeixeira, César uhttp://link.springer.com/10.1007/978-3-030-31635-801868nas a2200193 4500008004100000245005700041210005700098520130100155653001701456653001401473653002501487653002101512100002101533700002001554700001701574700002201591700002001613856004101633 2019 eng d00aStatistical parametric synthesis of budgerigar songs0 aStatistical parametric synthesis of budgerigar songs3 a

In this paper we present the synthesis of budgerigar songs with Hidden Markov Models (HMMs) and the HMM-based Speech Synthesis System (HTS). Budgerigars can produce complex and diverse sounds that are difficult to categorize. We adapted tech- niques that are commonly used in the area of speech synthe- sis so that we can use them for the synthesis of budgerigar songs. To segment the recordings, the songs are broken down into phrases, which are sounds separated by silence. Complex phrases furthermore can be subdivided into smaller units and then be clustered to identify recurring elements. These ele- ment categories along with additional contextual information are used together to enhance the training and synthesis. Over- all, the aim of the process is to offer an interface that gener- ates new sequences and compositions of bird songs based on user input, consisting of the desired song structure and contex- tual information. Finally, an objective evaluation comparing the synthesized output to the natural recording is performed, and a subjective evaluation with human listeners shows that they pre- fer resynthesized over natural recordings and that they perceive no significant differences in terms of naturalness between natu- ral, resynthesized, and synthesized versions.

10abioacoustics10abird song10aHMM- based synthesis10aspeech synthesis1 aGutscher, Lorenz1 aPucher, Michael1 aLozo, Carina1 aHoeschele, Marisa1 aMann, Daniel, C uhttps://bio.acousti.ca/ja/node/5758402063nas a2200193 4500008004100000245006900041210006800110520147000178653001401648653001201662653001301674653001201687653004601699100002601745700002201771700001701793700001801810856004101828 2019 eng d00aWhy did solid otoliths evolve in the ears of modern bony fishes?0 aWhy did solid otoliths evolve in the ears of modern bony fishes3 a

Modern bony fishes (Teleostei), which comprise almost one-half of all extant vertebrate species, show a remarkable diversity in ear morphology, including otolith shape. Fish bioacousticians are still puzzling over the question of why solid calcareous otoliths with species-specific shapes evolved, whereas most “non-teleost” vertebrates possess numerous tiny otoconia. This question is linked to when and how often a switch from loosely aggregated material towards a solid structure—and from apatite to calcium carbonate—occurred during the vertebrate radiation and whether those character shifts are related to altered hearing. In a recent study, we constructed a hypothetical framework for otolith evolution by compiling the available information on the structure of otoliths and otoconia in > 160 species covering all major vertebrate groups. We concluded that solid teleost otoliths may have initially evolved as a selectively neutral by-product of other key innovations, and that the teleost-specific genome duplication event may have facilitated their subsequent diversification. Differences in otolith mass and shape might have enabled the perception of different ranges of acoustic information and may have evolved during the diversification of auditory abilities. In some teleost groups, otolith morphology may have co-evolved with ancillary hearing structures, especially if ears are closely connected to a gas bladder.

10aaragonite10ahearing10aotoconia10aotolith10ateleost-specific genome duplication event1 aSchulz-Mirbach, Tanja1 aLadich, Friedrich1 aHeß, Martin1 aPlath, Martin uhttps://bio.acousti.ca/ja/node/5742601731nas a2200145 4500008004100000245006400041210006400105520128300169653001301452653002401465653001601489100001801505700002101523856004101544 2019 eng d00aPropagation of bird vocalizations in the Alpine environment0 aPropagation of bird vocalizations in the Alpine environment3 a

Rock ptarmigan is a bird living in the mountains tops, whose population tends to decrease in Europe over the last decade, notably due to climate change, habitat loss and human disturbance. Censusing of number of birds in the Alps is realized via point-count monitoring using birds vocalization. However, detection of bird vocalizations by the human hear is somewhat tricky in these non-homogeneous landforms, due to sound propagation effects. In order to improve the counting method, it is necessary to understand how bird vocalizations propagate in the Alpine environment. With this aim, a propagation model based on a ray-tracing approach is developed and includes topography, ground reflection and absorption and atmospheric refraction and absorption. The model is first validated in both frequency and time domains against reference results obtained with a numerical solution of the linearized Euler equations for simple cases. Propagation of the bird vocalization in the Alpine environment is then illustrated. It is shown that the active space of the bird dramatically depends on the environment. The modeling of active and detection space will provide precise information for the birds monitoring, enabling managers to define more precisely their counting plans.

10aethology10aOutdoor propagation10aRay tracing1 aBerger, Loïc1 aSebe, Frédéric uhttps://bio.acousti.ca/ja/node/5742201691nas a2200133 4500008004100000245005800041210004800099520128400147653001401431653003001445653002001475100002101495856004101516 2019 eng d00a The Cormorant Ear – Adapted to Underwater Hearing?0 aCormorant Ear Adapted to Underwater Hearing3 a

Diving birds may spend several minutes underwater during foraging dives. However, surprisingly little is known about avian underwater hearing. We do not know their sensitivity or even if they respond to underwater sound. To help filling this gap we measured the audiograms of cormorants (Phalacrocorax carbo sinensis) and studied their ear anatomy. Wild-caught fledglings were anesthetized and their auditory brainstem response (ABR) to clicks and tone bursts was measured, first in an anechoic box in air and then in a large water-filled tank with their head and neck submerged 10 cm below the surface. The overall shape of their air-audiograms was like that reported for birds of the same size in air. The bandwidth and slopes of their audiograms were similar in air and water. However, in air the highest sensitivity was found at 2 kHz, whereas it was displaced towards lower frequencies underwater. These results suggest that cormorants have rather poor in-air hearing compared to similar-sized birds. Their underwater hearing sensitivity, however, is higher than what would have been expected for purely air-adapted ears. A possible reason for the poor in-air sensitivity is the special ear anatomy with the central eardrum shaped as a rigid piston like in turtles.

10aAudiogram10aAuditory threshold curves10aGreat cormorant1 aWahlberg, Magnus uhttps://bio.acousti.ca/ja/node/5742101291nas a2200169 4500008004100000245007000041210006900111520077400180653001700954653001800971653002000989100001601009700001601025700001901041700002001060856004101080 2019 eng d00aNew aspects in birdsong recognition utilizing the gabor transform0 aNew aspects in birdsong recognition utilizing the gabor transfor3 a

In this paper we will be concerned with mathematical methods for birdsong recognition and classification. Current approaches compute the spectrogram of an audio recording using the Gabor transform, which is then used as input for a convolutional neural network (CNN) to classify the recording. While recent work is dedicated to finding the best hyperparameters for training the CNN and for data augmentation, the parameters for the Gabor transform and the signal detection methods receive less attention. We aim to close this gap by evaluating the effect of different window lengths on the overall classification accuracy. Additionally we propose a method for denoising signals based on quantiles to account for different signal to noise ratios in the dataset.

10abioacoustics10aDeep learning10aGabor transform1 aHEUER, Sven1 aTAFO, Pavel1 aHOLZMANN, Hajo1 aDahlke, Stephan uhttps://bio.acousti.ca/ja/node/5742001975nas a2200205 4500008004100000245009300041210006900134520129400203653001801497653003101515653003601546100002101582700001801603700001601621700002101637700002901658700002001687700002101707856004101728 2019 eng d00aApplying convolutional neural networks to the analysis of mouse ultrasonic vocalizations0 aApplying convolutional neural networks to the analysis of mouse 3 a

Many species in diverse taxonomic groups, including rodents, bats, and insects, communicate with complex ultrasonic vocalizations (USVs) (>20 kHz). Two main components of processing and analyzing USV recordings include detection and classification of syllable types. Recently we developed an efficient algorithm for detecting mouse USVs (Automatic Mouse Ultrasound Detector (A-MUD)). The main challenge is detecting USVs under conditions with a low signal-to-noise ratio, while minimizing rates of false positives (FP). Mice produce many short USVs (< 10 millisecond) that inflate FPs. We aimed to improve the detection of mouse USVs with A-MUD by classifying vocalizations into three discrete syllable types (with 0, 1, or ≥2 frequency-jumps) or FP. Supervised Convolutional Neural Networks (CNNs) were fed by 2D Gammatone Spectrograms (GSs) adapted to the frequency range of mice. Evaluation of performance shows that CNNs yielded an overall accuracy of 95±1.2% and macro-F1 score of 90±2.7%. In contrast, multilayer feed-forward neural networks fed by vectorized spectrograms provided an overall accuracy of only 85.4±1.9% and macro-F1 score of 75.4±2.9%, and therefore, the chosen CNNs outperformed this conventional classification method.

10aDeep learning10aImage-based classification10aUltrasonic vocalizations (USVs)1 aAbbasi, Reyhaneh1 aBalazs, Peter1 aNOLL, Anton1 aNICOLAKIS, Doris1 aMarconi, Maria, Adelaide1 aZala, Sarah, M.1 aPenn, Dustin, J. uhttps://bio.acousti.ca/ja/node/5741901140nas a2200121 4500008004100000245014000041210006900181520066500250100001900915700002600934700001700960856004100977 2019 eng d00aAdaptation of British Standards to Identify Construction Site Activity Noise Sources with the Potential to Cause Stress to Giant Pandas0 aAdaptation of British Standards to Identify Construction Site Ac3 a

Giant pandas have a broader hearing range than humans and have higher sensitivity in different frequency bands. Giant pandas are known to become stressed when subjected to undesirable noise, therefore noise which humans may deem unobtrusive has the potential to cause stress in giant pandas. As giant panda breeding programmes are taking place in zoos throughout the world it is important to understand the impact that anthropogenic noise has on these mammals and how it affects their wellbeing. This paper discusses the adaptation from international standards on noise to appropriately address the impact from construction site noise on giant pandas.

1 aSNAITH, Murray1 aRODRIGUEZ, Alessandro1 aMARMO, Brett uhttps://bio.acousti.ca/ja/node/5741800505nas a2200169 4500008004100000020001800041245002200059210002100081260005900102100002100161700002200182700001900204700001900223700002400242700002100266856004800287 2018 eng d a978145036188000aEcosound-explorer0 aEcosoundexplorer aMelbourne, AustraliaNew York, New York, USAbACM Press1 aBuchanan, George1 aStevenson, Duncan1 aRowe, Benjamin1 aZhang, Jinglan1 aTowsey, Michael, W.1 aBrereton, Margot uhttp://dl.acm.org/citation.cfm?doid=329214702775nas a2200097 4500008004100000245006300041210006300104520245000167100001902617856004102636 2010 eng d00aAcoustic sensing in snapping shrimp dominated environments0 aAcoustic sensing in snapping shrimp dominated environments3 a

Snapping shrimp dominate the high frequency soundscape in shallow warm waters. The noises produced by these small creatures are a result of the collapse of cavitation bubbles they produce. During the rapid collapse, the temperatures in the bubble can momentarily reach the surface temperature of the sun, and produce impulsive noise with source levels higher than 190 dB re 1 μPa @ 1m. With millions of snapping shrimp in most warm shallow water environments, the resulting cacophony is heard in the form of a background crackle familiar to many tropical divers. The resulting ambient noise has highly non-Gaussian statistics. What implications does this have on acoustic sensing in these environments? Can signal processing techniques developed with Gaussian noise assumptions be used without significant penalty in these environments? Can these shrimp be used as sources of opportunity for sensing? To begin answering some of these questions, we present a review of some of the research on signal processing in impulsive noise. Snapping shrimp noise is modeled accurately by symmetric α-stable distributions. Optimal signal processing in α-stable noise is often computationally infeasible, but computationally simple near-optimal solutions can be applied with gains up to 5-10 dB. Communicating in environments with snapping shrimp noise has its own challenges. The errors due to the impulsive noise on sub-carriers of a multi-carrier communication system, or the in-phase and quadrature channels of a single carrier system are not independent. If handled inappropriately, forward error correction codes can perform poorly in such systems. However, if the dependence in the errors can be characterized, it can be exploited in the decoding process to get substantial communication performance gains. We show this through an information theoretic analysis of the communication channel with additive symmetric α-stable noise. Finally, we turn to some applications where the snapping shrimp sounds can be used as sources of opportunity. They can serve as “illumination” for ambient noise imaging, where underwater objects can be imaged completely passively. They can also be used as sources for geoacoustic inversion of the surface sediment. We present some results from past experiments to show how sediment sound speed can indeed be inferred by simply listening passively to the cacophony of the shrimp.

1 aChitre, Mandar uhttps://bio.acousti.ca/ja/node/5351001958nas a2200145 4500008004100000245008700041210006900128260003000197520145800227100001801685700002401703700001601727700001901743856005001762 2018 eng d00aAnimal Call Recognition with Acoustic Indices: Little Spotted Kiwi as a Case Study0 aAnimal Call Recognition with Acoustic Indices Little Spotted Kiw aCanberra, AustraliabIEEE3 a

Long-duration recordings of the natural environment are very useful in monitoring of animal diversity. After accumulating weeks or even months of recordings, ecologists need an efficient tool to recognize species in those recordings. Automated species recognizers are developed to interpret field-collected recordings and quickly identify species. However, the repetitive work of designing and selecting features for different species is becoming a serious problem for ecologists. This situation creates a demand for generic recognizers that perform well on multiple animal calls. Meanwhile, acoustic indices are proposed to summarize the structure and distribution of acoustic energy in natural environment recordings. They are designed to assess the acoustic activity of animal habitats and do not have discrimination against any species. That characteristic makes them natural generic features for recognizers. In this study, we explore the potential of acoustic indices being generic features and build a kiwi call recognizer with them as a case study. We proposed a kiwi call recognizer built with a Multilayer Perceptron (MLP) classifier and acoustic index features. Experimental results on 13 hours of kiwi call recordings show that our recognizer performs well, in terms of precision, recall and F1 measure. This study shows that acoustic indices have the potential of being generic features that can discriminate multiple animal calls.

1 aGan, Hongxiao1 aTowsey, Michael, W.1 aLi, Yuefeng1 aZhang, Jinglan uhttps://ieeexplore.ieee.org/document/8615857/01294nas a2200157 4500008004100000245007800041210006900119260002600188520079200214100001701006700001401023700001801037700001701055700001401072856005001086 2018 eng d00aClassification of Cetacean Whistles Based on Convolutional Neural Network0 aClassification of Cetacean Whistles Based on Convolutional Neura aHangzhou, ChinabIEEE3 a

Vocal communication is a primary communication method of cetaceans. Learning the language of them is of great significance for the protection of cetaceans, and it also provides support for acoustic study of cetaceans’ biological behavior. In this study, a classification method based on deep learning is proposed for the classification of cetacean whistles. Firstly, the method performs short-time Fourier transform on whistles to obtain the time-frequency distribution, and then uses the deep learning model, convolutional neural network, to classify the signal based on time-frequency characteristics. The simulation results show that this method has a relatively high classification accuracy when choosing the appropriate parameters, indicating the method is effective.

1 aLiu, Songzuo1 aLiu, Meng1 aWang, Mengjia1 aMa, Tianlong1 aQing, Xin uhttps://ieeexplore.ieee.org/document/8555732/01270nas a2200133 4500008004100000245007300041210006900114260002400183520080800207100002901015700002101044700002101065856005001086 2018 eng d00aAcoustic Diversity Classifier for Automated Marine Big Data Analysis0 aAcoustic Diversity Classifier for Automated Marine Big Data Anal aVolos, GreecebIEEE3 a

In recent years, big data has increasingly drawn the attention of the R&D community. With the advent of marine data, monitoring marine big data becomes a new trend that advocates for assessing human impact on marine data. Nevertheless, there is a lack of support for acoustic sounds classification in such environment, covering diverse data that can exist (i.e., fish sounds, human activities sounds and environmental sounds). In this paper, we cope with this gap by proposing a deep learning-based approach that enables to efficiently classify these acoustic sounds aiming at automating the support of marine sound analysis in big data architectures. A set of experiments have been conducted using a real marine dataset to demonstrate the feasibility and the effectiveness of our approach.

1 aBelghith, Emna, Hachicha1 aRioult, Francois1 aBouzidi, Medjber uhttps://ieeexplore.ieee.org/document/8576027/02068nas a2200193 4500008004100000245011100041210007300152260001000225520137100235653001601606653003501622653001701657653003001674653002801704100002001732700002501752700003501777856006201812 2018 eng d00aPré-processamento de sinais acústicos para análise e caracterização de vocalizações de lobos-guará0 aPréprocessamento de sinais acústicos para análise e caracterizaç bGaloa3 a

The possibility of automatic species identification through their communication acoustic signals opens new possibilities for the study of behavior and the preservation of biodiversity. Although commercially available, automated analysis tools still lack success in terms of outcome and accuracy. The success of an automated method requires the validation of a process sequencing strategy aiming at the determination of vocal acoustic parameters in the middle of a complex soundscape. A challenge in this regard lies in the extraction of noise from field recordings, which sometimes makes difficult the correct interpretation of acoustic parameters. In this study, we explore a combination of signal pre-processing steps to extract the noise of recordings of roar bark vocalizations of maned wolves (Chrysocyon brachyurus) in recordings made by a digital recorder sampled at 44.1 kHz with 16-bit resolution, using processing tools of the software Audiosculpt 3.2.7 by IRCAM. The procedure involved a sequence of steps: selection of the best audios and file segmentation; loudness normalization; identification and removal of noise zones. The results include processing over 10 hours of field recording with the production of a body of more than 131 vocalizations, under conditions suitable for the individual characterization analysis that will be done next.

10aAudiosculpt10aautomatic individual detection10abioacoustics10abiodiversity conservation10asound signal processing1 aFerreira, Bruna1 aFaria, Régis, Rossi1 aMonticelli, Patricia, Ferreira uhttps://proceedings.science/proceedings/113/_papers/8715901651nas a2200169 4500008004100000245010900041210006900150260003100219520107500250653001601325653001701341653001701358653001301375100001901388700001901407856005501426 2018 eng d00aMorphometric and bioacoustic analysis Gaga chicken (Gallus gallus domesticus) at Bangkalan, Kamal Madura0 aMorphometric and bioacoustic analysis Gaga chicken Gallus gallus aBali, IndonesiabAuthor(s)3 a

Gaga chicken was known as local chicken, which has potential in the business of ornamental chicken in Indonesia. Gaga chicken has two types crowing sound. Three-dangdut types and seven slow types were collected from several stockbreeding in Bangkalan, Kamal Madura. The aim of the research is to investigate the biodiversity of Gaga’ chicken based on bioacoustics and morphometric measurement. The data were analyzed by Mann Withney analysis. The variables measured were neck length, body weight, femur length, tibia length, shank length, shank diameter, superior maxilla, wing length, comb height, the third length, and chest bone length. The parameters were measured, recorded, and analyzed for crowing duration and number of crowing using the voice recording tool and Ashampoo Music Studio 6 software. The results showed that dangdut type 215 g was bigger than slow type 197 g. Average crowing duration dangdut type were 7,67 second, with longest syllable were 9 syllable and crowing duration slow type were 6,71 with longest syllable were 10 syllable.

10aBioacoustic10aGaga Chicken10aMorphometric10aSyllable1 aZulistiana, T.1 aAbinawanto, A. uhttp://aip.scitation.org/doi/abs/10.1063/1.506413901560nas a2200133 4500008004100000020001800041245007100059210006900130260005300199520107200252100003501324700001901359856004801378 2018 eng d a978145036482900aAutomatic Ecosystem Identification Using Psychoacoustical Features0 aAutomatic Ecosystem Identification Using Psychoacoustical Featur aUnion, NJ, USANew York, New York, USAbACM Press3 a

The recent changes in worldwide ecosystems require constant monitoring and actions to prevent habitat destruction and mass extinction of species. The development of Passive Acoustic Monitoring (PAM) techniques has allowed the study of ecosystem dynamics, producing no harm to them. In this study, a relation between psychoacoustical features and ecosystem degradation was explored. Psychoacoustical features are used mainly for urban soundscapes categorization and they are based on human subjective perception of sound; however, they provide a starting framework for linking soundscape to spatial structure. To map soundscape to ecosystem health, an artificial neural network (ANN) and three different types of support vector machines (SVM) were tested for automatic ecosystem type identification using the selected features. Three out of four models leaded to good results, but as future work, it is suggested to adapt psychoacoustical features to a more neutral auditory system so the analysis includes more species perception of the ecosystem soundscape.

1 aDuque-Montoya, Diana, Carolina1 aIsaza, Claudia uhttp://dl.acm.org/citation.cfm?doid=324325002054nas a2200229 4500008004100000245006100041210006000102520141500162653001701577653001801594653002301612653002301635653000801658100001301666700001701679700002101696700001401717700001601731700001601747700002001763856004101783 2015 eng d00aMulti-disciplinary approach for forest health monitoring0 aMultidisciplinary approach for forest health monitoring3 aRecent occurrence of unfortunate series of events such as flash flood, landslides and unprecedented warmer temperature raised concerns and drove actions towards preventing the occurrence of such events. Biodiversity monitoring is one of the alternative solutions which is a long term effort that provide useful information to allow early prevention of unfortunate events as a result of illegal logging activities, deforestation, forest fire etc. The existing biodiversity monitoring are manually conducted which rely on human resource and as such introduced several challenges and limitations. Therefore, the development of an efficient, real-time biodiversity monitoring system is needed. This paper discussed the challenges and successful implementation of wireless biodiversity monitoring system which encompasses knowledge and expertise from multi-disciplinary field such as environmental, biology, electronics and network engineering. This paper also provided information on sensors and wireless networks utilized in this monitoring system. With the availability of this biodiversity monitoring system, the status of the forest health can be identified on real- time basis hence early precaution and prevention can be undertaken to prevent the catastrophic events. 10abioacoustics10aforest health10ainternet of things10aweather monitoring10aWSN1 aAzmi, N.1 aRazali, M.H.1 aKamaruddin, L.M.1 aHarun, A.1 aRahim, N.A.1 aZakaria, A.1 aShakaff, A.Y.M. uhttps://bio.acousti.ca/ja/node/47719