7 papers · 1 filter
Music Flamingo: Scaling Music Understanding in Audio Language Models
Sreyan Ghosh, Arushi Goel, Lasha Koroshinadze +8
We introduce Music Flamingo, a novel large audio-language model designed to advance music (including song) understanding in foundational audio models. While audio-language research…
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…
MMAU-Pro: A Challenging and Comprehensive Benchmark for Holistic Evaluation of Audio General Intelligence
Sonal Kumar, Å imon SedláÄek, Vaibhavi Lokegaonkar +31
Audio comprehension-including speech, non-speech sounds, and music-is essential for achieving human-level intelligence. Consequently, AI agents must demonstrate holistic audio unde…
Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data
Sreyan Ghosh, Sonal Kumar, Zhifeng Kong +3
We present Synthio, a novel approach for augmenting small-scale audio classification datasets with synthetic data. Our goal is to improve audio classification accuracy with limited…
ProSE: Diffusion Priors for Speech Enhancement
Sonal Kumar, Sreyan Ghosh, Utkarsh Tyagi +4
Speech enhancement (SE) is the foundational task of enhancing the clarity and quality of speech in the presence of non-stationary additive noise. While deterministic deep learning…
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…