Shotgun Microphone Research Articles

Drone audition for bioacoustic monitoring

Abstract Multi‐rotor drones equipped with acoustic sensors have great potential for bioacoustically monitoring vocal species in the environment for biodiversity conservation. The bottleneck of this emerging technology is the ego‐noise from the rotating motors and propellers, which can completely mask the target sound and make sound recordings unusable for further analysis. The ego‐noise not only degrades the performance of bioacoustic monitoring but also impacts the behaviour of target species if the drone is too close to the target area. In this paper, we address this challenging problem by combining hardware and software solutions that minimize the impact of drone ego‐noise on bioacoustic monitoring. To collect the target sound from the ground, we used a shotgun microphone recording system suspended underneath the drone body with a wire rope (steel fishing line) of length 2 m. The suspended rope puts a large distance between the drone and the recorder, reducing the propeller sound perceived by the microphone. The shotgun microphone enables the sound to be picked up from the ground effectively while rejecting the drone sound from above. We further developed a software solution that aims to automatically recognize the bird species from the bird call recording and we proposed a noise‐augmented training scheme to improve the robustness of bird recognition in the presence of strong drone noise. We evaluated the performance of the system in a test problem of recognizing 20 bird species with in‐flight recordings, where a loudspeaker on the ground simulates bird calls. The recordings were obtained using a drone hovering at various altitudes ranging from 5 to 30 m. By combining the hardware and software solutions, the system recognizes birds robustly at an altitude of 30 m and signal‐to‐noise ratio −25 dB. This demonstrates the feasibility of our drone audition system for bioacoustic monitoring. The proposed method overcomes a long‐standing bottleneck problem in drone audition and promises new applications of bioacoustic monitoring in research and management.

Comparison of foot strike sound between rearfoot, midfoot and forefoot strike runners.

There are three common foot strike techniques in runners. Whether these techniques generate different sounds at the point of impact with the ground may influence lower limb kinetics. No previous studies have determined whether such relationships exist. To determine foot-ground impact sound characteristics and to compare the impact sound characteristics across foot strike techniques and the relationships between impact sound characteristics and vertical loading rates. Cross-sectional study Setting: Gait analysis laboratory Patients or Other Participants: Thirty runners (50% female, age=23.5±4.0 yrs, mass=58.1±8.2kg, height=1.67±0.1m) completed overground running trials with rearfoot strike (RFS), midfoot strike (MFS) and forefoot strike (FFS) techniques in a gait analysis laboratory. Impact sound was measured by a shotgun microphone and the peak sound amplitude, median frequency and sound duration were analysed. Separate linear regression, clustering participants repeated measures were used to compare the sound parameters across foot strike techniques. Kinetic data was collected from a force plate and the vertical loading rates were calculated. Pearson's correlation was used to determine relationship between sound characteristic and kinetics. Landing with a MFS or FFS resulted in greater peak sound amplitude (ps<0.001) and shorter sound duration (ps<0.001) than RFS. MFS exhibited the highest median frequency among the three foot strike patterns, followed by FFS (ps<0.001). We did not find a significant relationship between vertical loading rates and any impact sound parameters (ps>0.115). The results suggest that impact sound characteristics may be used to differentiate foot strike patterns in runners. However, this did not relate to lower limb kinetics. Therefore, clinicians should not solely rely on impact sound to infer impact loading.

Field test comparison of various acoustic drone detection methods

Acoustics methods for Unmanned Aerial Systems (UAS) detection have several advantages. They are low cost and passive, do not radiate any RF signals, and can provide UAS classification. The disadvantages of acoustic methods include shorter detection distances and susceptibility to acoustic noise. We present the results of field tests of several acoustic UAS detection methods. The tested systems included the Drone Acoustic Detection System (DADS) that was developed by Stevens Institute of Technology, a 16 microphone cross two-tier acoustic array, directional acoustic microphones (parabolic and shotgun microphones), and the OptiNav ACAM 120 acoustic array. The field tests were conducted to investigate the performance of various acoustic systems for UAS detection and tracking ability of various DJI models. Directional microphones and systems with many microphones did not demonstrate a significant advantage over the lower cost DADS that consists of three nodes, with each node having four microphones. Cross-correlation of signals between various microphone pairs is used for finding the acoustic signal direction of arrival. This system provides acoustic target detection and tracking. Classification software discriminates between a UAS and other possible targets, such as airplanes, helicopters, and ground vehicles. [Work supported by Air Force Research Laboratory under Contract No. FA8750-17-C-0190.]

Optimization of acoustic drone detection based on tests with linear acoustic array

In a number of field tests for Unmanned Aerial Systems (UAS) acoustic detection, we used several detection systems including a 16 microphone cross two-tier acoustic array, directional acoustic microphones (parabolic microphones and shotgun microphones), and the OptiNav ACAM 120 acoustic array. The improvement of the detection distance using direction microphones and microphone arrays was less than what was estimated based on the system directivity index. A possible limitation of the directional system performance can be due to wind noise, presence of various noise sources and atmospheric turbulence conditions. The turbulence leads to decorrelation of the acoustic signal received by various elements of a microphone array. The UAS and noise signals recorded by the cross two-tier AFRL acoustic array was used for estimation of external noise and UAS signal correlation depending of the distances between microphones. The array is shaped like a two-tier cross, with each tier spanning 3 m and pseudo-logarithmic spacing between the elements. The coherence measurements between various microphone pairs were used for the estimation of the optimal size of a microphone array for UAS detection and optimal sensor separation for the Stevens Drone Acoustic Detection System (DADS). [Work supported by Air Force Research Laboratory under Contract No. FA8750-17-C-0190.]

Design of an unmanned aerial vehicle mounted system for quiet audio recording

This paper describes the design of an unmanned aerial vehicle (UAV) mounted system for recording sound from a targeted source or direction with a minimum amount of noise. The objective of the study is: i) select an optimum electric motor-propeller combination which minimises the level of unwanted noise from these components at the microphone positions; ii) design a microphone array configuration suitable for installation on a UAV; and iii) develop a signal processing algorithm that significantly reduces noise in the recording. The designed system was prototyped and tested in various scenarios simulated in an anechoic chamber as well as by recordings collected from a system mounted on a hovering UAV. The system succeeded in reducing the propeller noise level up to approximately 12 dB compared to the recording by a shotgun microphone. Results of subjective listening tests suggest the quality of the recording made by the designed UAV mounted system is significantly better than that of the recording by the shotgun microphone.

Alarm call modification by prairie dogs in the presence of juveniles

While several drivers of wildlife alarm calls have been identified, recent work on the impact of the audience on the plasticity of alarm calling indicates that intraspecific communication can drive this behavior. We build on this literature by assessing changes in call characteristics in black-tailed prairie dogs (Cynomys ludovicianus) in the presence of recently emerged juveniles. Alarm calls were elicited by approaching individuals, and then recorded using a shotgun microphone. Presence and distance of pups were noted prior to recording. Alarm calls were analyzed for changes in spectral and temporal characteristics relative to those of adults that were not in the immediate presence of pups. Our analyses indicated that adult prairie dogs lowered the central concentration of energy in their alarm calls when calling in the presence of pups. This may show that prairie dogs are conscious of the type of alarm call produced based on the behavioral context of calling and potentially the audience receiving the message. Furthermore, this may support the hypothesis that alarm calling is intended to reach conspecifics, rather than to send a message to the predator itself.

Classification of chestnuts according to moisture levels using impact sound analysis and machine learning

In this study, a prototype system was designed, built and tested to classify chestnuts using impact sound signals and machine learning methods according to moisture contents. Briefly, the system consisted of a shotgun microphone, a sliding platform, an impact surface, a triggering system, a sound device and a computer. Sound signal data were acquired from 2028 chestnut samples with three different moisture levels. Acoustic signals from chestnut samples were filtered to alleviate negative effects of unwanted noise. Four machine learning classifiers using three different feature sets obtained from two feature groups applying feature reduction methods were trained and tested to classify pairs of chestnut moisture group categories as 35% versus 45%, 35% versus 55%, 45% versus 55% (classification with two outputs) and 35% versus 45% versus 55% (classification with three outputs), respectively. The highest classification success (88%) was achieved for the classification application category of 35 versus 55%.

Sound, Space and Bodies: Building Relations in the Work of Invisible Flock and Atelier Bildraum

In this article, I discuss sounds potential to construct fictional spaces and build relations between bodies using two performance installations as case studies. The first is Invisible Flock’s 105+dB, a site-specific sound work which transports crowd recordings of a soccer match to alternative geographical locations. The second is Atelier Bildraum’s Bildraum, an installation performance using live photography, architectural models and ambient sound. By writing through these two works, I question how sound builds relations between bodies and across space as well as questioning the role of site within sound installation works.

An evaluation of speech reconstruction for degraded speech of optical microphone with deep neural network

Measuring distant-talking speech with high accuracy is important in detecting criminal activity. Various microphones such as the parabolic and shotgun microphones have been developed for measuring it. However, most of them have difficulty in extracting distant-talking speech at a target position if they are surrounded by noisy sound sources. Therefore, this study focuses on a microphone system to extract the distant-talking speech by vibrating a papery object using laser light. This system is referred to as an optical microphone in this study. The sound quality of the optical microphone is especially degraded at higher frequencies because it utilizes an external diaphragm consisting of various materials as the vibrating papery object. In this study, we therefore propose a reconstruction method for degraded distant-talking speech observed with the optical microphone. The method is realized by using a deep neural network (DNN) that is trained as the system between clean and observed speech signals. In the proposed method, the log-power spectra of 11 frames are used for the input of the DNN. Finally, we confirmed the effectiveness of the proposed system through an evaluation experiment.

When glitches make good art

Two women make their way painstakingly around a cramped apartment, moving in sync with each other in a sort of techno-tango. Ziv Schneider steadily passes a discontinued PrimeSense Carmine 3D scanner over rows of picture frames, pots, and pans. Its infrared sensors take in the curves and divots of the tiny studio apartment. Caitlin Robinson tails her, shotgun microphone in hand, carrying a computer that's tethered to her partner's scanner by a USB cable

Refined acoustic modeling and analysis of shotgun microphones

A shotgun microphone is a highly directional pickup device widely used in noisy environments. The key element that leads to its superior directivity is a tube with multiple slot openings along its length. One traditional way to model the directional response of a shotgun is to assume plane waves traveling in the tube as if it is in the free field. However, the frequency response and directivity predicted by this traveling wave model can differ drastically from practical measurements. In this paper, an in-depth electroacoustic analysis was conducted to examine the problem by considering the standing waves inside the tube with an analogous circuit containing phased pressure sources and T-networks of tube segments. A further refinement is to model the housing diffraction effect with the aid of the equivalent source method (ESM). The on-axis frequency response and directivity pattern predicted by the proposed model are in close agreement with the measurements. From the results, a peculiar bifurcation phenomenon of directivity pattern at the Helmholtz frequency was also noted. While the shotgun behaves like an endfire array above the Helmholtz frequency, it becomes a broadside array below the Helmholtz frequency. The standing wave effect can be mitigated by covering the slot openings with mesh screen, which was found to alter the shotgun response to be closer to that of the traveling wave model above a critical frequency predicted by the half-wavelength rule. A mode-switching model was developed to predict the directional responses of mesh-treated shotguns.

Modeling and optimization of a shotgun condenser microphone

This paper is focused on modeling and optimization of a shotgun microphone that is known to be a highly directional acoustic pick-up. A lumped-parameter model is established, with the aid of Zuckerwar's approach, to predict the frequency response of the condenser microphone. On the basis of the model, we use the simulated annealing ([SA]) method to optimize the microphone parameters, including the diaphragm radius, the diaphragm thickness, the air gap distance and the volume of back chamber, such that the sensitivity is maximized subject to a desired bandwidth. In our modified approach, the air gap resistance (Ra ) and the back chamber compliance (Cbc ) are used to calculate the D factor in Zuckerwar's model. To model the shotgun tube, T circuit and two-port network are utilized in formulating transfer matrices that is then converted to an impedance matrix representation. In addition, an array model is established to simulate the directional response. The results revealed that the shotgun microphone is highly directional at high frequencies, while the on-axis frequency response is influenced by the acoustic resonances of the tube. The simulation results suggest that the tube length should be greater than half of the wavelength, whereas and the spacing between holes should be less than half of the wavelength.

A Vocal-Based Analytical Method for Goose Behaviour Recognition

Since human-wildlife conflicts are increasing, the development of cost-effective methods for reducing damage or conflict levels is important in wildlife management. A wide range of devices to detect and deter animals causing conflict are used for this purpose, although their effectiveness is often highly variable, due to habituation to disruptive or disturbing stimuli. Automated recognition of behaviours could form a critical component of a system capable of altering the disruptive stimuli to avoid this. In this paper we present a novel method to automatically recognise goose behaviour based on vocalisations from flocks of free-living barnacle geese (Branta leucopsis). The geese were observed and recorded in a natural environment, using a shielded shotgun microphone. The classification used Support Vector Machines (SVMs), which had been trained with labeled data. Greenwood Function Cepstral Coefficients (GFCC) were used as features for the pattern recognition algorithm, as they can be adjusted to the hearing capabilities of different species. Three behaviours are classified based in this approach, and the method achieves a good recognition of foraging behaviour (86–97% sensitivity, 89–98% precision) and a reasonable recognition of flushing (79–86%, 66–80%) and landing behaviour(73–91%, 79–92%). The Support Vector Machine has proven to be a robust classifier for this kind of classification, as generality and non-linear capabilities are important. We conclude that vocalisations can be used to automatically detect behaviour of conflict wildlife species, and as such, may be used as an integrated part of a wildlife management system.

Effects of microphone and loudspeaker directivity on accuracy of synthesized wave fronts in sound field reproduction based on wave field synthesis

Sound field reproduction based on wave field synthesis proposed by Camras [M. Camras, J. Acoust. Soc. Am. 43, 1425–1431 (1968)] is a technique that synthesizes wave fronts of a control area at a listening area using directional microphones and loudspeakers placed at the boundary of those areas. This study evaluates the effects of the directivity of microphones and loudspeakers on the accuracy of synthesized wave fronts. Microphones and loudspeakers were placed at the boundary of both areas that have two cases (a circle with a radius of 2 m and a square 4 m on a side). The number of microphones and loudspeakers were 630 (circle) and 801 (square). The interval of microphones and loudspeakers was less than 2 cm. Therefore, spatial aliasing does not occur if the frequency is less than 8 kHz. Three directional patterns (omnidirectional, unidirectional, and shotgun) were designed as directivity conditions of microphones and loudspeakers. Computer simulation results showed that there is no effect of directivity of loudspeakers and that accurate wave fronts can be reproduced when a unidirectional or shotgun microphone is applied. [Work supported by special grant for education and research of Tokyo Univ. of Agriculture and Technol.]

Superdirectivity design for a sphere-buffled microphone array

For the signal extraction from a diffuse sound field, the superdirecitonal microphone array seems to be more stable and more effective than the noise canceling microphone array system. In this research, for the sphere-baffled microphone array (SBM), the superdirectivity characteristic was designed by the frequency domain beamforming method and the complex least mean square algorithm. The frequency domain beamforming is a method for a broadband beamforming. There is a possibility of improvement of the directivity frequency characteristic. The SBM is an array which was embedded 36 elements on the rigid diffractive sphere of 8.84 cm radius. An advantage of SBM is its isotropy. When the directivity characteristic was fixed for a definite direction, only the shift coefficent can be used to change the mainlobe direction. This idea can be easily generalized into the three-dimensional mainlobe control. In a typical design calculation, for the beamwidth of −3 dB, 30° was achieved at the frequency 2 kHz. This characteristic is comparable to that of a larger size microphone, which is called a shotgun microphone.

Voice and Taxonomy of Caprimulgus (rufus) otiosus (Caprimulgidae), with a Reevaluation of Caprimulgus rufus Subspecies

The St. Lucia Nightjar (Caprimulgus otiosus) exhibits minimal vocal and plumage differentiation from mainland forms of the Rufous Nightjar (C. rufus), and, therefore, we consider otiosus conspecific with rufus. Caprimulgus rufus otiosus appears to be resident on the northeastern section of St. Lucia, Lesser Antilles; specimen records from Venezuela are considered erroneous. We recognize the following described subspecies: otiosus (St. Lucia), minimus (Costa Rica to N. Venezuela), rufus (NW Brazil, S. Venezuela, east through the Guianas, and south to south of the Rio Amazonas), and rutilus (S. Brazil, N. Argentina, E. Bolivia). Resumen. Las vocalizaciones y el plumaje del tapacaminos de Santa Lucia {Caprimulgus otiosus) y de la forma continental C. rufus, son muy parecidas, por lo que se les considera como conespecificos. Caprimulgus rufus otiosus aparentemente es residente de la seccion noreste de Santa Lucia en las Antillas Menores; consideramos que los registros de Venezuela son erroneos. Nosotros reconocemos las siguientes subespecies descritas: otiosus (Santa Lucia), minimus (de Costa Rica al N de Venezuela), rufus (NW Brazil, S Venezuela, E de las Guyanas hasta el lado sur del Rio Amazonas), y rutilus (S Brazil, N Argentina y E Bolivia). In the latest A.O.U. Check-list (1983), the Lesser Antillean form (otiosus) of the wide-ranging Rufous Nightjar (Caprimulgus rufus) was elevated to species status. Previously, the St. Lucia Nightjar (C. otiosus) had been regarded as an isolated subspecies of C. rufus by most authors (Bangs 1911; Cory 1918; Griscom and Greenway 1937; Peters 1940; Bond 1947, 1959, 1977), although Wetmore and Phelps (1953) believed that otiosus deserved specific recognition. The A.O.U. (1983) gave the following rationale for treatment of otiosus as a species, . . it seems best to retain C. otiosus as specifically distinct until its status is determined. Herein we demonstrate that otiosus shows minimal vocal and plumage differentiation from mainland forms of C. rufus, and is best treated as a subspecies of C. rufus. METHODS AND MATERIALS Study skins were accumulated at the Academy of Natural Sciences, Philadelphia (ANSP) for plumage color and pattern comparisons. Wing chord and length of central rectrices were taken using dial calipers to the nearest 0.1 mm. All tape recordings of otiosus were made on the windward side of St. Lucia, West Indies on 7 May 1988 and 29 April 1989. Tape recordings were made using a Sony TCM 5000 cassette recorder, with a Sennheiser ME 80 shotgun microphone. Additional recordings were obtained from Hardy et al. (1988). Sonagrams were produced with SoundEdit of Farallon Computing, Inc., Emeryville, California, and Canary of the Bioacoustics Research Program at the Cornell Laboratory of Ornithology, Ithaca, New York.