Improving detection of acoustic signals by means of a time and frequency multiple energy detectors

Standard energy detectors (ED) are optimum to detect unknown signals in presence of uncorrelated Gaussian noise. However, in real applications the signal duration and bandwidth are unpredictable and this fact can considerably degrade the detection performance if the appropriate observation vector length is not correctly selected. Therefore, a multiple energy detector (MED) structure is applied in the time as well as in the frequency domain and it is evaluated in real acoustic scenarios. The results obtained demonstrate the robustness of the MED structure and a performance improvement in comparison to the standard ED. © 2011 IEEE.Manuscript received March 01, 2011; revised May 26, 2011; accepted May 29, 2011. Date of publication June 07, 2011; date of current version June 17, 2011. This work was supported by the Spanish Administration and the FEDER Programme of the EC under Grant TEC 2008-02975, and by the Generalitat Valenciana under Grant PROMETEO/2010/040. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Saeed Sanei.Moragues Escrivá, J.; Serrano Cartagena, A.; Vergara Domínguez, L.; Gosálbez Castillo, J. (2011). Improving detection of acoustic signals by means of a time and frequency multiple energy detectors. IEEE Signal Processing Letters. 18(8):458-461. https://doi.org/10.1109/LSP.2011.2158644S45846118

A target guided subband filter for acoustic event detection in noisy environments using wavelet packets

This paper deals with acoustic event detection (AED), such as screams, gunshots, and explosions, in noisy environments. The main aim is to improve the detection performance under adverse conditions with a very low signal-to-noise ratio (SNR). A novel filtering method combined with an energy detector is presented. The wavelet packet transform (WPT) is first used for time-frequency representation of the acoustic signals. The proposed filter in the wavelet packet domain then uses a priori knowledge of the target event and an estimate of noise features to selectively suppress the background noise. It is in fact a content-aware band-pass filter which can automatically pass the frequency bands that are more significant in the target than in the noise. Theoretical analysis shows that the proposed filtering method is capable of enhancing the target content while suppressing the background noise for signals with a low SNR. A condition to increase the probability of correct detection is also obtained. Experiments have been carried out on a large dataset of acoustic events that are contaminated by different types of environmental noise and white noise with varying SNRs. Results show that the proposed method is more robust and better adapted to noise than ordinary energy detectors, and it can work even with an SNR as low as -15 dB. A practical system for real time processing and multi-target detection is also proposed in this work

The next detectors for gravitational wave astronomy

This paper focuses on the next detectors for gravitational wave astronomy which will be required after the current ground based detectors have completed their initial observations, and probably achieved the first direct detection of gravitational waves. The next detectors will need to have greater sensitivity, while also enabling the world array of detectors to have improved angular resolution to allow localisation of signal sources. Sect. 1 of this paper begins by reviewing proposals for the next ground based detectors, and presents an analysis of the sensitivity of an 8 km armlength detector, which is proposed as a safe and cost-effective means to attain a 4-fold improvement in sensitivity. The scientific benefits of creating a pair of such detectors in China and Australia is emphasised. Sect. 2 of this paper discusses the high performance suspension systems for test masses that will be an essential component for future detectors, while sect. 3 discusses solutions to the problem of Newtonian noise which arise from fluctuations in gravity gradient forces acting on test masses. Such gravitational perturbations cannot be shielded, and set limits to low frequency sensitivity unless measured and suppressed. Sects. 4 and 5 address critical operational technologies that will be ongoing issues in future detectors. Sect. 4 addresses the design of thermal compensation systems needed in all high optical power interferometers operating at room temperature. Parametric instability control is addressed in sect. 5. Only recently proven to occur in Advanced LIGO, parametric instability phenomenon brings both risks and opportunities for future detectors. The path to future enhancements of detectors will come from quantum measurement technologies. Sect. 6 focuses on the use of optomechanical devices for obtaining enhanced sensitivity, while sect. 7 reviews a range of quantum measurement options

Robust sound event detection in bioacoustic sensor networks

Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record sounds of wildlife over long periods of time in scalable and minimally invasive ways. Deriving per-species abundance estimates from these sensors requires detection, classification, and quantification of animal vocalizations as individual acoustic events. Yet, variability in ambient noise, both over time and across sensors, hinders the reliability of current automated systems for sound event detection (SED), such as convolutional neural networks (CNN) in the time-frequency domain. In this article, we develop, benchmark, and combine several machine listening techniques to improve the generalizability of SED models across heterogeneous acoustic environments. As a case study, we consider the problem of detecting avian flight calls from a ten-hour recording of nocturnal bird migration, recorded by a network of six ARUs in the presence of heterogeneous background noise. Starting from a CNN yielding state-of-the-art accuracy on this task, we introduce two noise adaptation techniques, respectively integrating short-term (60 milliseconds) and long-term (30 minutes) context. First, we apply per-channel energy normalization (PCEN) in the time-frequency domain, which applies short-term automatic gain control to every subband in the mel-frequency spectrogram. Secondly, we replace the last dense layer in the network by a context-adaptive neural network (CA-NN) layer. Combining them yields state-of-the-art results that are unmatched by artificial data augmentation alone. We release a pre-trained version of our best performing system under the name of BirdVoxDetect, a ready-to-use detector of avian flight calls in field recordings.Comment: 32 pages, in English. Submitted to PLOS ONE journal in February 2019; revised August 2019; published October 201

MEMS-Based Terahertz Photoacoustic Chemical Sensing System

Advancements in microelectromechanical system (MEMS) technology over the last several decades has been a driving force behind miniaturizing and improving sensor designs. In this work, a specialized cantilever pressure sensor was designed, modeled, and fabricated to investigate the photoacoustic (PA) response of gases to terahertz (THz) radiation under low-vacuum conditions associated with high-resolution spectroscopy. Microfabricated cantilever devices made using silicon-on-insulator (SOI) wafers were tested in a custom-built test chamber in this first ever demonstration of a cantilever-based PA chemical sensor and spectroscopy system in the THz frequency regime. The THz radiation source was amplitude modulated to excite acoustic waves in the chamber, and PA molecular spectroscopy of a gas species was performed. An optical measurement technique was used to evaluate the PA effect on the cantilever sensor; a laser beam was reflected off the cantilever tip and through an iris to a photodiode. As the cantilever movement deflected the laser beam, the beam was clipped by an iris and generated the PA signal. Experimental data indicated a predominantly linear response in signal amplitude from the photodiode measurement technique, which directly correlated to measured cantilever deflections. Using the custom-designed PA chamber and MEMS cantilever sensor, excellent low-pressure PA spectral data of methyl cyanide (CH3CN) at 2 to 40 mTorr range has been obtained. At low chamber pressures, the sensitivity of our system was 1.97 × 10−5 cm−1 and had an excellent normalized noise equivalent absorption (NNEA) coefficient of 1.39 × 10−9 cm−1 W Hz-½ using a 0.5 s signal averaging time

Microwave apparatus for gravitational waves observation

In this report the theoretical and experimental activities for the development of superconducting microwave cavities for the detection of gravitational waves are presented.Comment: 42 pages, 28 figure