AI Medical Compendium Journal:
The Journal of the Acoustical Society of America

Showing 21 to 30 of 100 articles

Biodiversity assessment using passive acoustic recordings from off-reef location-Unsupervised learning to classify fish vocalization.

The Journal of the Acoustical Society of America
We present the quantitative characterization of Grande Island's off-reef acoustic environment within the Zuari estuary during the pre-monsoon period. Passive acoustic recordings reveal prominent fish choruses. Detailed characteristics of the call emp...

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...

Pathological voice classification based on multi-domain features and deep hierarchical extreme learning machine.

The Journal of the Acoustical Society of America
The intelligent data-driven screening of pathological voice signals is a non-invasive and real-time tool for computer-aided diagnosis that has attracted increasing attention from researchers and clinicians. In this paper, the authors propose multi-do...

Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles.

The Journal of the Acoustical Society of America
This work presents an open-source matlab software package for exploiting recent advances in extracting tonal signals from large acoustic data sets. A whistle extraction algorithm published by Li, Liu, Palmer, Fleishman, Gillespie, Nosal, Shiu, Klinck...

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...

Morphologic clustering of earcanals using deep learning algorithm to design artificial ears dedicated to earplug attenuation measurement.

The Journal of the Acoustical Society of America
Designing earplugs adapted for the widest number of earcanals requires acoustical test fixtures (ATFs) geometrically representative of the population. Most existing ATFs are equipped with unique sized straight cylindrical earcanals, considered repres...

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...

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...

A model of speech recognition for hearing-impaired listeners based on deep learning.

The Journal of the Acoustical Society of America
Automatic speech recognition (ASR) has made major progress based on deep machine learning, which motivated the use of deep neural networks (DNNs) as perception models and specifically to predict human speech recognition (HSR). This study investigates...