Overview: AI-generated music often sounds too perfect, with a steady pitch, a rigid rhythm, and a lack of human flaws.Repetitive loops, odd textures, and unnatu ...

This study used deep neural networks (DNN) to reconstruct voice information (viz., speaker identity), from fMRI responses in the auditory cortex and temporal voice areas, and assessed the ...

ABSTRACT: The study adapts several machine-learning and deep-learning architectures to recognize 63 traditional instruments in weakly labelled, polyphonic audio synthesized from the proprietary Sound ...

Attention mechanisms are very useful innovations in the field of artificial intelligence (AI) for processing sequential data, especially in speech and audio applications. This FAQ talks about how ...

The increasing ability of deep learning models to produce realistic-sounding synthetic speech poses serious problems for privacy, public trust, and digital security. To c...Show More The increasing ...

I've been digging into the audio preprocessing in transformers.js and noticed an issue: There are currently no unit tests for the audio_utils module in the JS implementation. The output of spectrogram ...

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That's an excellent work. However I have some difficullties. As I am going the finetune only some parts of the model, I need to calculate some intermediate data. Specifically, given an audio sequence, ...

Abstract: This study analyzes techniques for compressing generative autoencoders to enable their deployment on resource-constrained devices, addressing the challenges and optimizations required for ...

Introduction: Anxiety and depression reduce autonomic system activity, as measured by Heart Rate Variability (HRV), and exacerbate cardiac morbidity. Both music and mindfulness have been shown to ...