So yeah, I vibe-coded a log colorizer—and I feel good about it

Oh, sure, I can “code.” That is, I can flail my way through a block of (relatively simple) pseudocode and follow the flow. I ...
Frontiers

Detection of AI-Generated Audio: Speech, Environmental Sound, Music, and Beyond

Audio deepfakes, by definition, are synthetic audio recordings generated using deep learning-based systems for either malicious, artistic, or entertainment ...
GitHub

MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix

We introduce MMAR, a new benchmark designed to evaluate the deep reasoning capabilities of Audio-Language Models (ALMs) across massive multi-disciplinary tasks. MMAR comprises 1,000 meticulously ...
IEEE

Multimodal Interpretable Depression Analysis Using Visual, Physiological, Audio and Textual Data

Abstract: Motivated by depression's significant impact on global health, this work proposes MultiDepNet, a novel multi-modal interpretable depression detection system integrating visual, physiological ...
IEEE

FloodNet-Lite: A Lightweight Deep Learning for Flood Mapping Using Remote Sensing Data With Optimized UNet and Edge Deployment Approach in 6G

Abstract: Flood mapping using remote sensing data is critical to disaster response, especially in real-time monitoring and edge deployment. However, existing deep-learning (DL) models often face ...
MIT Technology Review

Using unstructured data to fuel enterprise AI success

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...