Passive acoustics is an effective method for monitoring marine mammals, facilitating both detection and population estimation. In warm tropical waters, this technique encounters challenges due to the high persistent level of ambient impulsive noise o...
The Journal of the Acoustical Society of America
38884525
For cochlear implant (CI) listeners, holding a conversation in noisy and reverberant environments is often challenging. Deep-learning algorithms can potentially mitigate these difficulties by enhancing speech in everyday listening environments. This ...
Cochlear implants (CIs) do not offer the same level of effectiveness in noisy environments as in quiet settings. Current single-microphone noise reduction algorithms in hearing aids and CIs only remove predictable, stationary noise, and are ineffecti...
The Journal of the Acoustical Society of America
39082692
Understanding speech in noisy environments is a challenging task, especially in communication situations with several competing speakers. Despite their ongoing improvement, assistive listening devices and speech processing approaches still do not per...
Passive Acoustic Monitoring (PAM), which involves using autonomous record units for studying wildlife behaviour and distribution, often requires handling big acoustic datasets collected over extended periods. While these data offer invaluable insight...
Neural networks : the official journal of the International Neural Network Society
39255636
Single-channel speech enhancement primarily relies on deep learning models to recover clean speech signals from noise-contaminated speech. These models establish a mapping relationship between noisy and clean speech. However, considering the sparse d...
Neural networks : the official journal of the International Neural Network Society
39316951
The recent Generative Fixed-filter Active Noise Control (GFANC) method achieves a good trade-off between noise reduction performance and system stability. However, labelling noise data for training the Convolutional Neural Network (CNN) in GFANC is t...
When investigating the relationship between the acoustic environment and human wellbeing, there is a potential problem resulting from data source self-correlation. To address this data source self-correlation problem, we proposed a third-party assess...
This research aims to use the power of geospatial artificial intelligence (GeoAI), employing the categorical boosting (CatBoost) machine learning model in conjunction with two metaheuristic algorithms, the firefly algorithm (CatBoost-FA) and the frui...
The Journal of the Acoustical Society of America
39248559
A speech intelligibility (SI) prediction model is proposed that includes an auditory preprocessing component based on the physiological anatomy and activity of the human ear, a hierarchical spiking neural network, and a decision back-end processing b...