In the fast-evolving landscape of artificial intelligence, a new framework called Omni-AutoThink is making waves by tackling a persistent challenge in multimodal reasoning. Developed by a team of researchers including Dongchao Yang, Songxiang Liu, Di
In the world of speech and singing quality assessment, subjective mean opinion scores (MOS) have long been the gold standard. However, MOS has its limitations. It’s a single number that doesn’t account for the diverse expectations of users, ignores s
In the ever-evolving landscape of music technology, a groundbreaking development has emerged that promises to revolutionize the way we perceive and manipulate singing voices. A team of researchers, including Gongyu Chen, Xiaoyu Zhang, Zhenqiang Weng,
In the ever-evolving landscape of audio technology, researchers are constantly seeking innovative ways to improve self-supervised learning (SSL) models. A recent study by Kohei Yamamoto and Kosuke Okusa introduces Aliasing-aware Patch Embedding (AaPE
In the ever-evolving landscape of music and audio technology, a groundbreaking advancement has emerged that could redefine how we classify and understand lyrical content. Researchers have introduced a novel approach to feature fusion within the Trans
Respiratory diseases are a significant global health concern, and traditional methods of diagnosis through auscultation—listening to the lungs with a stethoscope—often fall short due to subjectivity, environmental noise, and variability among clinici
In the world of music technology, the quest for expressive music performance rendering has always been a significant challenge. Traditionally, researchers have relied on supervised learning methods, which require large amounts of labeled data. Howeve
Multi-modal large language models (MLLMs) have become a cornerstone in the AI landscape, seamlessly integrating text, images, and audio to power a wide array of applications. However, their growing popularity has cast a spotlight on a critical vulner
Sentiment analysis is a powerful tool in the world of technology, allowing machines to understand and interpret human emotions. Traditionally, this has been done through text analysis, but the field of multimodal sentiment analysis (MSA) is expanding
In the ever-evolving landscape of music production, a groundbreaking development has emerged that promises to revolutionize the way we approach post-production. Researchers have introduced LLM2Fx-Tools, a multimodal tool-calling framework designed to
