Search papers, labs, and topics across Lattice.
7 papers published across 0 labs.
Self-supervised speech embeddings unlock substantial gains in cross-speaker dysarthria detection during awake craniotomy, outperforming handcrafted features by up to 26.1% AUC.
Frontier MLLMs exhibit strong local perception but falter on long-horizon audio-visual reasoning, with a single benchmark exposing specific failure modes like identity drift and cross-modal misalignment.
Complex-valued fusion of audio-visual embeddings unlocks significant gains in open-vocabulary event localization, surpassing prior methods by up to 6.6% Event-F1.
Decouple complex audio scenes into individual, controllable sound sources directly from a single generative model.
Audio-language models excel at identifying sounds but fail to grasp the crucial context of how speakers react to them.
Self-supervised speech embeddings unlock substantial gains in cross-speaker dysarthria detection during awake craniotomy, outperforming handcrafted features by up to 26.1% AUC.
Frontier MLLMs exhibit strong local perception but falter on long-horizon audio-visual reasoning, with a single benchmark exposing specific failure modes like identity drift and cross-modal misalignment.
Complex-valued fusion of audio-visual embeddings unlocks significant gains in open-vocabulary event localization, surpassing prior methods by up to 6.6% Event-F1.
Decouple complex audio scenes into individual, controllable sound sources directly from a single generative model.
Audio-language models excel at identifying sounds but fail to grasp the crucial context of how speakers react to them.
Fine-grained emotion control in TTS is now achievable at inference time with minimal speaker or content degradation, bypassing the need for expensive model retraining.
Black-box text-to-music generators can be steered to precisely match complex user intent by an agent that iteratively refines prompts based on rubric-based audio verification.
