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Sound

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Data driven source localization using a library of nearby shipping sources of opportunity.

JASA express letters
A library of broadband (100-1000 Hz) channel impulse responses (CIRs) estimated between a short bottom-mounted vertical line array (VLA) in the Santa Barbara channel and selected locations along the tracks of 27 isolated transiting ships, cumulated o...

Physics-informed neural networks for one-dimensional sound field predictions with parameterized sources and impedance boundaries.

JASA express letters
Realistic sound is essential in virtual environments, such as computer games and mixed reality. Efficient and accurate numerical methods for pre-calculating acoustics have been developed over the last decade; however, pre-calculating acoustics makes ...

A Cough-based deep learning framework for detecting COVID-19.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a deep learning framework for detecting COVID-19 positive subjects from their cough sounds. In particular, the proposed approach comprises two main steps. In the first step, we generate a feature representing the cough sound by co...

Stress Inference from Abdominal Sounds using Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Stress is often considered the 21 century's epidemic, affecting more than a third of the globe's population. Long-term exposure to stress has significant side effects on physical and mental health. In this work we propose a methodology for detecting ...

Neural network for multi-exponential sound energy decay analysis.

The Journal of the Acoustical Society of America
An established model for sound energy decay functions (EDFs) is the superposition of multiple exponentials and a noise term. This work proposes a neural-network-based approach for estimating the model parameters from EDFs. The network is trained on s...

A Parallel Classification Model for Marine Mammal Sounds Based on Multi-Dimensional Feature Extraction and Data Augmentation.

Sensors (Basel, Switzerland)
Due to the poor visibility of the deep-sea environment, acoustic signals are often collected and analyzed to explore the behavior of marine species. With the progress of underwater signal-acquisition technology, the amount of acoustic data obtained f...

A Prediction Model of Defecation Based on BP Neural Network and Bowel Sound Signal Features.

Sensors (Basel, Switzerland)
(1) Background: Incontinence and its complications pose great difficulties in the care of the disabled. Currently, invasive incontinence monitoring methods are too invasive, expensive, and bulky to be widely used. Compared with previous methods, bowe...

Polyphonic Sound Event Detection Using Temporal-Frequency Attention and Feature Space Attention.

Sensors (Basel, Switzerland)
The complexity of polyphonic sounds imposes numerous challenges on their classification. Especially in real life, polyphonic sound events have discontinuity and unstable time-frequency variations. Traditional single acoustic features cannot character...

Empirical Mode Decomposition-Based Feature Extraction for Environmental Sound Classification.

Sensors (Basel, Switzerland)
In environment sound classification, log Mel band energies (MBEs) are considered as the most successful and commonly used features for classification. The underlying algorithm, fast Fourier transform (FFT), is valid under certain restrictions. In thi...

A Two-Mode Underwater Smart Sensor Object for Precision Aquaculture Based on AIoT Technology.

Sensors (Basel, Switzerland)
Monitoring the status of culture fish is an essential task for precision aquaculture using a smart underwater imaging device as a non-intrusive way of sensing to monitor freely swimming fish even in turbid or low-ambient-light waters. This paper deve...