activity
20242026
collaborators

9 papers

eess.AS2026

Audio-Visual Flamingo: Open Audio-Visual Intelligence for Long and Complex Videos

Sreyan Ghosh, Arushi Goel, Kaousheik Jayakumar +19

We present Audio-Visual Flamingo (AV-Flamingo), a fully open state-of-the-art audio-visual large language model (AV-LLM) for joint understanding and reasoning over audio, images, a…

cs.SD2026

Multi-Domain Audio Question Answering Benchmark Toward Acoustic Content Reasoning

Chao-Han Huck Yang, Sreyan Ghosh, Qing Wang +14

We present Task 5 of the DCASE 2025 Challenge: an Audio Question Answering (AQA) benchmark spanning multiple domains of sound understanding. This task defines three QA subsets (Bio…

eess.AS2025

SPUR: A Plug-and-Play Framework for Integrating Spatial Audio Understanding and Reasoning into Large Audio-Language Models

S Sakshi, Vaibhavi Lokegaonkar, Neil Zhang +4

Spatial perception is central to auditory intelligence, enabling accurate understanding of real-world acoustic scenes and advancing human-level perception of the world around us. W…

cs.SD2025

Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities

Sreyan Ghosh, Zhifeng Kong, Sonal Kumar +6

Understanding and reasoning over non-speech sounds and music are crucial for both humans and AI agents to interact effectively with their environments. In this paper, we introduce…

eess.AS2024

MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark

S Sakshi, Utkarsh Tyagi, Sonal Kumar +6

The ability to comprehend audio--which includes speech, non-speech sounds, and music--is crucial for AI agents to interact effectively with the world. We present MMAU, a novel benc…

cs.SD2024

EH-MAM: Easy-to-Hard Masked Acoustic Modeling for Self-Supervised Speech Representation Learning

Ashish Seth, Ramaneswaran Selvakumar, S Sakshi +3

In this paper, we present EH-MAM (Easy-to-Hard adaptive Masked Acoustic Modeling), a novel self-supervised learning approach for speech representation learning. In contrast to the…