AIMC Topic: Sound

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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 ...

Open set classification strategies for long-term environmental field recordings for bird species recognition.

The Journal of the Acoustical Society of America
Deep learning is one established tool for carrying out classification tasks on complex, multi-dimensional data. Since audio recordings contain a frequency and temporal component, long-term monitoring of bioacoustics recordings is made more feasible w...

Lightweight deep convolutional neural network for background sound classification in speech signals.

The Journal of the Acoustical Society of America
Recognizing background information in human speech signals is a task that is extremely useful in a wide range of practical applications, and many articles on background sound classification have been published. It has not, however, been addressed wit...

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 ...

Non-invasive Detection of Bowel Sounds in Real-life Settings Using Spectrogram Zeros and Autoencoding.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Gastrointestinal (GI) diseases are amongst the most painful and dangerous clinical cases, due to inefficient recognition of symptoms and thus, lack of early-diagnostic tools. The analysis of bowel sounds (BS) has been fundamental for GI diseases, how...

Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Tinnitus is attributed by the perception of a sound without any physical source causing the symptom. Symptom profiles of tinnitus patients are characterized by a large heterogeneity, which is a major obstacle in developing general treatments for this...

Crackle Detection In Lung Sounds Using Transfer Learning And Multi-Input Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Large annotated lung sound databases are publicly available and might be used to train algorithms for diagnosis systems. However, it might be a challenge to develop a well-performing algorithm for small non-public data, which have only a few subjects...

ConvNets for counting: Object detection of transient phenomena in steelpan drums.

The Journal of the Acoustical Society of America
We train an object detector built from convolutional neural networks to count interference fringes in elliptical antinode regions in frames of high-speed video recordings of transient oscillations in Caribbean steelpan drums, illuminated by electroni...

New Avenues in Audio Intelligence: Towards Holistic Real-life Audio Understanding.

Trends in hearing
Computer audition (i.e., intelligent audio) has made great strides in recent years; however, it is still far from achieving holistic hearing abilities, which more appropriately mimic human-like understanding. Within an audio scene, a human listener i...