@conference {58227, title = {The sound of one hand}, year = {2002}, abstract = {

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.

}, isbn = {1581134541}, doi = {10.1145/50644310.1145/506443.506566}, url = {http://portal.acm.org/citation.cfm?doid=506443}, author = {Amento, Brian and Hill, Will and Terveen, Loren} } @conference {58034, title = {Social Network Analysis of an Acoustic Environment: The Use of Visualised Data to Characterise Natural Habitats}, year = {2019}, abstract = {

(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.

}, doi = {10.1109/DICTA47822.201910.1109/DICTA47822.2019.8945963}, url = {https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8943071https://ieeexplore.ieee.org/document/8945963/}, author = {Wang, Junling and Sankupellay, Mangalam and Konovalov, Dmitry and Towsey, Michael and Roe, Paul} } @conference {58003, title = {Assessing the effect of aquatic noise on fish behavior and physiology: a meta-analysis approach}, booktitle = {Fourth International Conference on the Effects of Noise on Aquatic Life}, year = {2016}, publisher = {Acoustical Society of America}, organization = {Acoustical Society of America}, address = {Dublin, Ireland}, abstract = {

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.

}, doi = {10.1121/2.0000291}, url = {http://asa.scitation.org/doi/abs/10.1121/2.0000291}, author = {Cox, Kieran D. and Brennan, Lawrence P. and Dudas, Sarah E. and Juanes, Francis} } @conference {57991, title = {Sound reception and radiation in a small insect}, booktitle = {Acoustics 2012}, year = {2012}, address = {Nantes, France}, abstract = {

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.

}, author = {Mhatre, Natasha and Montealegre-Z, Fernando and Rohini Balakrishnan and Daniel Robert} } @conference {57937, title = {Sound Transduction in the Auditory System of Bushcrickets}, year = {2011}, abstract = {

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.

}, keywords = {LDV-measurements, tonotopy, traveling wave}, doi = {10.1063/1.3658131}, url = {http://aip.scitation.org/doi/abs/10.1063/1.3658131}, author = {Nowotny, Manuela and Arun Palghat Udayashankar and Weber, Melanie and Hummel, Jennifer and K{\"o}ssl, Manfred} } @conference {57915, title = {Field testing and performance evaluation of the Long-term Acoustic Real-Time Sensor for Polar Areas (LARA)}, year = {2019}, abstract = {

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.

}, keywords = {arctic, bio-acoustics, profiling, real-time detections}, author = {H. Matsumoto and J. Haxel and B. Kahn and L. Roche and A. Turpin and Klinck, Holger and R.P. Dziak and J. Childress and K. Sexton and T. Nakamura} } @conference {57652, title = {Automatic Segmentation of Ultrasonic Vocalizations in Rodents}, year = {2019}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

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.

}, keywords = {Rodents ultrasonic vocalizations, Signal processing, Signal segmentation, Spectral Entropy}, isbn = {978-3-030-31634-1}, doi = {10.1007/978-3-030-31635-810.1007/978-3-030-31635-8_5}, url = {http://link.springer.com/10.1007/978-3-030-31635-8}, author = {Pessoa, Diogo and Petrella, Lorena and Castelo-Branco, Miguel and Teixeira, C{\'e}sar}, editor = {Henriques, Jorge and Neves, Nuno and de Carvalho, Paulo} } @conference {57584, title = {Statistical parametric synthesis of budgerigar songs}, year = {2019}, abstract = {

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.

}, keywords = {bioacoustics, bird song, HMM- based synthesis, speech synthesis}, author = {Gutscher, Lorenz and Pucher, Michael and Lozo, Carina and Hoeschele, Marisa and Mann, Daniel C} } @conference {57418, title = {Why did solid otoliths evolve in the ears of modern bony fishes?}, year = {2019}, abstract = {

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.

}, keywords = {aragonite, hearing, otoconia, otolith, teleost-specific genome duplication event}, author = {Tanja Schulz-Mirbach and Friedrich Ladich and Martin He{\ss} and Martin Plath} } @conference {57418, title = {Propagation of bird vocalizations in the Alpine environment}, year = {2019}, abstract = {

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.

}, keywords = {ethology, Outdoor propagation, Ray tracing}, author = {Lo{\"\i}c Berger and Fr{\'e}d{\'e}ric Sebe} } @conference {57418, title = { The Cormorant Ear {\textendash} Adapted to Underwater Hearing?}, year = {2019}, abstract = {

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.

}, keywords = {Audiogram, Auditory threshold curves, Great cormorant}, author = {Magnus Wahlberg} } @conference {57418, title = {New aspects in birdsong recognition utilizing the gabor transform}, year = {2019}, abstract = {

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.

}, keywords = {bioacoustics, Deep learning, Gabor transform}, author = {Sven HEUER and Pavel TAFO and Hajo HOLZMANN and Stephan Dahlke} } @conference {57418, title = {Applying convolutional neural networks to the analysis of mouse ultrasonic vocalizations}, year = {2019}, abstract = {

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.

}, keywords = {Deep learning, Image-based classification, Ultrasonic vocalizations (USVs)}, author = {Reyhaneh Abbasi and Peter Balazs and Anton NOLL and Doris NICOLAKIS and Maria Adelaide Marconi and Sarah M. Zala and Dustin J. Penn} } @conference {57418, title = {Adaptation of British Standards to Identify Construction Site Activity Noise Sources with the Potential to Cause Stress to Giant Pandas}, year = {2019}, abstract = {

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.

}, author = {Murray SNAITH and Alessandro RODRIGUEZ and Brett MARMO} } @conference {53524, title = {Ecosound-explorer}, booktitle = {the 30th Australian ConferenceProceedings of the 30th Australian Conference on Computer-Human Interaction - OzCHI {\textquoteright}18}, year = {2018}, publisher = {ACM Press}, organization = {ACM Press}, address = {Melbourne, AustraliaNew York, New York, USA}, isbn = {9781450361880}, doi = {10.1145/329214710.1145/3292147.3292238}, url = {http://dl.acm.org/citation.cfm?doid=3292147}, author = {Rowe, Benjamin and Zhang, Jinglan and Michael W. Towsey and Brereton, Margot} } @conference {53510, title = {Acoustic sensing in snapping shrimp dominated environments}, booktitle = {Proceedings of 20th International Congress on Acoustics, ICA}, year = {2010}, abstract = {

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.

}, author = {Chitre, Mandar} } @conference {53506, title = {Animal Call Recognition with Acoustic Indices: Little Spotted Kiwi as a Case Study}, booktitle = {2018 Digital Image Computing: Techniques and Applications (DICTA)2018 Digital Image Computing: Techniques and Applications (DICTA)}, year = {2018}, publisher = {IEEE}, organization = {IEEE}, address = {Canberra, Australia}, abstract = {

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.

}, doi = {10.1109/DICTA.2018.8615857}, url = {https://ieeexplore.ieee.org/document/8615857/}, author = {Gan, Hongxiao and Michael W. Towsey and Li, Yuefeng and Zhang, Jinglan} } @conference {53448, title = {Classification of Cetacean Whistles Based on Convolutional Neural Network}, booktitle = {2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)}, year = {2018}, publisher = {IEEE}, organization = {IEEE}, address = {Hangzhou, China}, abstract = {

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.

}, doi = {10.1109/WCSP.2018.8555732}, url = {https://ieeexplore.ieee.org/document/8555732/}, author = {Liu, Songzuo and Liu, Meng and Wang, Mengjia and Ma, Tianlong and Qing, Xin} } @conference {53441, title = {Acoustic Diversity Classifier for Automated Marine Big Data Analysis}, booktitle = {2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)}, year = {2018}, publisher = {IEEE}, organization = {IEEE}, address = {Volos, Greece}, abstract = {

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.

}, doi = {10.1109/ICTAI.2018.00029}, url = {https://ieeexplore.ieee.org/document/8576027/}, author = {Hachicha Belghith, Emna and Rioult, Francois and Bouzidi, Medjber} } @conference {53287, title = {Pr{\'e}-processamento de sinais ac{\'u}sticos para an{\'a}lise e caracteriza{\c c}{\~a}o de vocaliza{\c c}{\~o}es de lobos-guar{\'a}}, booktitle = {XXVIII ENCONTRO DA SOBRACXXVIII Encontro da SOBRAC}, year = {2018}, publisher = {Galoa}, organization = {Galoa}, abstract = {

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.

}, keywords = {Audiosculpt, automatic individual detection, bioacoustics, biodiversity conservation, sound signal processing}, doi = {10.17648/sobrac-87159}, url = {https://proceedings.science/proceedings/113/_papers/87159}, author = {Ferreira, Bruna and Rossi Faria, R{\'e}gis and Ferreira Monticelli, Patricia} } @conference {53258, title = {Morphometric and bioacoustic analysis Gaga chicken (Gallus gallus domesticus) at Bangkalan, Kamal Madura}, booktitle = {PROCEEDINGS OF THE 3RD INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2017 (ISCPMS2017)}, year = {2018}, publisher = {Author(s)}, organization = {Author(s)}, address = {Bali, Indonesia}, abstract = {

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.

}, keywords = {Bioacoustic, Gaga Chicken, Morphometric, Syllable}, doi = {10.1063/1.5064139}, url = {http://aip.scitation.org/doi/abs/10.1063/1.5064139}, author = {Zulistiana, T. and Abinawanto, A.} } @conference {53228, title = {Automatic Ecosystem Identification Using Psychoacoustical Features}, booktitle = {the International ConferenceProceedings of the International Conference on Pattern Recognition and Artificial Intelligence - PRAI 2018}, year = {2018}, publisher = {ACM Press}, organization = {ACM Press}, address = {Union, NJ, USANew York, New York, USA}, abstract = {

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.

}, isbn = {9781450364829}, doi = {10.1145/324325010.1145/3243250.3243251}, url = {http://dl.acm.org/citation.cfm?doid=3243250}, author = {Duque-Montoya, Diana Carolina and Isaza, Claudia} } @conference {47719, title = {Multi-disciplinary approach for forest health monitoring}, booktitle = {International Conference on Multidisiplinary Research and Innovation for Globally Sustainable Development}, year = {2015}, abstract = {Recent 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. }, keywords = {bioacoustics, forest health, internet of things, weather monitoring, WSN}, author = {N. Azmi and M.H. Razali and L.M. Kamaruddin and A. Harun and N.A. Rahim and A. Zakaria and A.Y.M. Shakaff} }