Skip to content

Nikeshbajaj/phyaat

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PhyAAt: Physiology of Auditory Attention

Predictive analysis of auditory attention from physiological signals


Documentation Status License: MIT PyPI version fury.io PyPI pyversions GitHub release PyPI format PyPI implementation HitCount GitHub commit activity Percentage of issues still open PyPI download month PyPI download week

Generic badge Ask Me Anything !

PyPI - Downloads


Table of contents


Requirement :

['numpy','scipy','matplotlib','spkit']

Installation

with pip

pip install phyaat

Build from the source

Download the repository or clone it with git, after cd in directory build it from source with

python setup.py install

Getting Started

For starting check here - Getting Started

Contents are being updated on the webpage continuously, please check there for updates


Cite As

@misc{bajaj2020phyaat,
      title={PhyAAt: Physiology of Auditory Attention to Speech Dataset}, 
      author={Nikesh Bajaj and Jesús Requena Carrión and Francesco Bellotti},
      year={2020},
      eprint={2005.11577},
      archivePrefix={arXiv},
      primaryClass={cs.HC}
}

Contacts:

PhD Student: Queen Mary University of London & University of Genoa