Summary: A large-scale study challenges the long-held belief that musical training boosts the brain’s earliest stages of sound processing. Using a sample size over four times larger than earlier ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Objective: This study aims to optimize monitor alarm sounds in the OR by integrating deep learning-based alarm classification (CNN + LSTM) with psychoacoustic modeling to reduce auditory fatigue and ...

This Collection invites research in AI applications for audio and video processing, focusing on novel architectures, cross-modal learning, performance optimization, and real-world applications.

this.video module is part of the "all.this" family, this.video standardizes video content for machine learning, ensuring seamless integration and interoperability. As part of the neurons.me ecosystem, ...

Given the recent surge in developments of deep learning, this paper provides a review of the state-of-the-art deep learning techniques for audio signal processing. Speech, music, and environmental ...

Computational models that mimic the structure and function of the human auditory system could help researchers design better hearing aids, cochlear implants, and brain-machine interfaces.

To sum it up, Using a comparative methodology, researchers demonstrate significant representational and computational similarities between speech-learning Deep Neural Networks (DNNs) and the human ...

The test battery appraises the overall wellbeing of the auditory system, starting with how sound is processed and perceived by the auditory system. The Auditory Processing (AP) test battery consists ...

These features could then be used as input to a deep learning network trained to classify the music into different genres, such as rock, jazz, or hip-hop. AudioFlux provides a comprehensive set of ...