AIMC Topic: Acoustics

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Deep learning assessment of syllable affiliation of intervocalic consonants.

The Journal of the Acoustical Society of America
In English, a sentence like "He made out our intentions." could be misperceived as "He may doubt our intentions." because the coda /d/ sounds like it has become the onset of the next syllable. The nature and occurrence condition of this resyllabifica...

A deep learning solution to the marginal stability problems of acoustic feedback systems for hearing aids.

The Journal of the Acoustical Society of America
For hearing aids, it is critical to reduce the acoustic coupling between the receiver and microphone to ensure that prescribed gains are below the maximum stable gain, thus preventing acoustic feedback. Methods for doing this include fixed and adapti...

[Current methods of acoustic analysis of voice: a review].

Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery
Acoustic analysis of the voice, as an objective, quantitative, non-invasive and reproducible method for the evaluation of voice quality, can be used to detect and analyze the acoustic characteristics of normal, artistic or pathological voice. With th...

Deep learning for assessing liver fibrosis based on acoustic nonlinearity maps: an in vivo study of rabbits.

Computer assisted surgery (Abingdon, England)
This study aimed to assess liver fibrosis in rabbits by deep learning models based on acoustic nonlinearity maps. Injection of carbon tetrachloride was used to induce liver fibrosis. Acoustic nonlinearity maps, which were built by data of echo signal...

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...

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 ...

Distinguishing multiple surface ships using one acoustic vector sensor based on a convolutional neural network.

JASA express letters
A direction of arrival (DOA) estimation method based on a convolutional neural network (CNN) using an acoustic vector sensor is proposed to distinguish multiple surface ships in a selected frequency band. The cross-spectrum of the pressure and partic...

Underwater single-channel acoustic signal multitarget recognition using convolutional neural networks.

The Journal of the Acoustical Society of America
The radiated noise from ships is of great significance to target recognition, and several deep learning methods have been developed for the recognition of underwater acoustic signals. Previous studies have focused on single-target recognition, with r...

Estimating vocal tract geometry from acoustic impedance using deep neural network.

JASA express letters
A data-driven approach using artificial neural networks is proposed to address the classic inverse area function problem, i.e., to determine the vocal tract geometry (modelled as a tube of nonuniform cylindrical cross-sections) from the vocal tract a...

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...