Representations of language in a model of visually grounded speech signal.
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analysis
data
experiments
imaginet
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README.md
setup.py

README.md

visually-grounded-speech

This repository contains code to reproduce the results from:

  • Chrupała, G., Gelderloos, L., & Alishahi, A. (2017). Representations of language in a model of visually grounded speech signal. ACL. arXiv preprint: https://arxiv.org/abs/1702.01991

Installation

First, download and install funktional version 0.6: https://github.com/gchrupala/funktional/releases/tag/0.6

Second, install the code in the current repo:

python setup.py develop

You also need to download and unpack the files data.tgz and models.tgz from http://doi.org/10.5281/zenodo.804392. The files in models.tgz contain the pre-trained models used for the analyses in the paper.

After unpacking these files you should have the directories data and models.

For the scripts in analysis, you also need to install:

  • sklearn
  • pandas
  • matplotlib
  • keras

Usage

Training models

In order to re-train one of the models, change to the corresponding directory in experiments, and execute:

python2.7 run.py > log.txt

Analysis

See analysis/README.md