Wildlife Acoustics, Inc.

Ian Agranat

Sherwood Kenneth Snyder

Andrew P Moroney

Aaron Grossman

Michael Cattafe

Steven M Johnson

Mark T Marini

Microphone housing

An apparatus includes a housing having a printed circuit board having a top surface and a bottom surface. The top surface of the printed circuit board forms an outer surface of the housing. The apparatus further includes a bottom-port microphone sensor mounted on the bottom surface of the printed circuit board. The printed circuit board has a port opening formed therein to provide an acoustic path from outside of the housing to the microphone sensor. A method of detecting ultrasonic signals includes receiving ultrasonic signals within a port opening of a printed circuit board forming part of a surface of a housing, and directing ultrasonic signals to a microphone sensor secured to a printed circuit board through the port of the printed circuit board.

Ultrasonic microphone enclosure

Methods and apparatus for recording and analyzing echolocation calls using zero crossing and/or digital sampling (full spectrum analysis) techniques, and for optimizing trigger thresholds used to activate recording in response to detection of an echolocation call.

Method and apparatus for detection of ultrasonic echolocation calls

An apparatus includes a housing having a horn with a mouth and a throat. The mouth of the horn is larger in cross section than the throat of the horn. The housing further includes a waveguide providing communication from the throat of the horn. The apparatus further includes a printed circuit board supported by the housing and a microphone sensor. The microphone sensor is mounted to a printed circuit board. The waveguide provides communication from the throat of the horn to the microphone sensor. The apparatus may be configured to include a housing having a waveguide providing communication to an interior of the housing, a printed circuit board supported by the housing within the interior of the housing, and a microphone sensor.

Audio recorder enclosure

Methods and apparatus for using Fourier techniques to detect and isolate the fundamental frequency sweep of echolocation calls produced by bats, or of other narrow-band whistles as produced by other kinds of animals such as birds and whales. According to one example, a Fourier transform is applied on blocks of input samples to produce output frames, and a narrowband frequency modulated signal is detected and traced through the output frames. A filter is applied in each frame to attenuate frequencies above or below the narrowband signal, and an inverse Fourier transform is applied to produce an output signal. The resulting signal may then be analyzed with zero crossing techniques to measure the precise instantaneous frequency sweep.

Method of extracting zero crossing data from full spectrum signals

A method and apparatus for measuring frequency and amplitude of an input signal representative of an echolocation call. In one example, a system includes a combination of a digital sampling channel and a zero crossing measurement channel that are configured to simultaneously measure the echolocation call and produce a combined, time-synchronous data set representative of the echolocation call.

Digital sampling and zero crossing of acoustic signals of animals

A method for listening to ultrasonic animal sound signals comprises: obtaining a plurality of input samples at an input sample rate, the plurality of input samples including at least one sequence of samples corresponding to an instance of an intermittently occurring animal sound signal; receiving a frame including at least two of the plurality of input samples; selecting a fraction of the samples as output samples, the fraction of the samples including a sample containing the at least one sequence of samples corresponding to an instance of an intermittently occurring animal sound signal; and transmitting the output samples at an output sample rate slower than the input sample rate.

Method for listening to ultrasonic animal sounds

A method and apparatus for powering a device, such as a data recorder or other device, according to an adjustable schedule. One example of the apparatus includes a programmable timer having an alarm output, a power regulator having an enable input coupled to the alarm output, a controller coupled to the power regulator and to the programmable timer, the controller being configured to receive operating power from the power regulator, and a powered device coupled to the power regulator and configured to receive power from the power regulator. The regulator has an operating state in which the operating power is provided to the powered device and an idle state in which the operating power is not provided to the powered device. The regulator is configured to be activated into the operating state by activation of the alarm output and deactivated into the idle state by deactivation of the alarm output, under the control of the controller.

Apparatus for scheduled low power autonomous data recording

Relatively powerful hand-held computing devices, Digital Signal Processors, Audio signal processing technology, voice recognition technology, expert systems, Hidden Markov Models, and/or neural networks are employed in a device capable of real-time automated species identification by listening to bird vocalizations in the field, analyzing their waveforms, and comparing these waveforms against known reference samples. An apparatus for identifying animal species from their vocalizations, comprises a source of digital signal representative of at least one animal candidate vocalization; a feature extractor that receives the digital signal, recognizes notes therein and extracts phrases including plural notes and that produces a parametric representation of the extracted phrases; and a comparison engine that receives the parametric representation of at least one of the digital signal and the extracted phrases, and produces an output signal representing information about the animal candidate based on a likely match between the animal candidate vocalization and known animal vocalizations. A computer-implemented method of identifying animal species, comprises: obtaining a digital signal representing a vocalization by a candidate animal; transforming the digital signal into a parametric representation thereof; extracting from the parametric representation a sequence of notes defining a phrase; comparing the phrase to phrases known to be produced by a plurality of possible animal species; and identifying a most likely match for the vocalization by the candidate animal based upon the comparison. The comparison engine or comparison function may use Hidden Markov Models, expert systems and/or neural networks.

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Concord, MA, United States of America

Ian Agranat