Search Results for author:
Found 4 papers, 2 papers with code
Contextual Feature Extraction Hierarchies Converge in Large Language Models and the Brain
We also compare the feature extraction pathways of the LLMs to each other and identify new ways in which high-performing models have converged toward similar hierarchical processing mechanisms.
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
In this paper, we present StyleTTS 2, a text-to-speech (TTS) model that leverages style diffusion and adversarial training with large speech language models (SLMs) to achieve human-level TTS synthesis.
naplib-python: Neural Acoustic Data Processing and Analysis Tools in Python
Recently, the computational neuroscience community has pushed for more transparent and reproducible methods across the field.
mvlearn: Multiview Machine Learning in Python
As data are generated more and more from multiple disparate sources, multiview data sets, where each sample has features in distinct views, have ballooned in recent years.
