John Kean explains how the xHE-AAC codec utilizes metadata to shift dynamic range control from content producers to listeners ...

T5Gemma 2 follows the same adaptation idea introduced in T5Gemma, initialize an encoder-decoder model from a decoder-only checkpoint, then adapt with UL2. In the above figure the research team show ...

Hello, I was trying to understand the importance of the modules in your framework and accordingly I was following the instructions given in the ablation study. This is how I changed the code as per ...

A new brain-computer interface can decode a person's inner speech, which could help people with paralysis communicate. When you purchase through links on our site, we may earn an affiliate commission.

I've been transcoding videos on handbrake using AV1 which I think is the latest encoder. AV1 on the Mac is often incredibly efficient. I'm talking 3gb -> 300mb efficient. Even tougher material with ...

Beyond tumor-shed markers: AI driven tumor-educated polymorphonuclear granulocytes monitoring for multi-cancer early detection. Clinical outcomes of a prospective multicenter study evaluating a ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more The University of California, Santa Cruz ...

Introduction: In the past decade, artificial neural networks (ANNs) have revolutionized many AI-related fields, including Speech Enhancement (SE). However, achieving high performance with ANNs often ...

Diffusion Transformers have demonstrated outstanding performance in image generation tasks, surpassing traditional models, including GANs and autoregressive architectures. They operate by gradually ...

Abstract: Speech enhancement (SE) models based on deep neural networks (DNNs) have shown excellent denoising performance. However, mainstream SE models often have high structural complexity and large ...