EntityKG (Entity Knowledge Graph)

This repository contains the codebase for the wav2graph paper:

wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech

https://arxiv.org/pdf/2408.04174.pdf

Project Overview

The wav2graph paper presents a novel approach to constructing entity knowledge graphs from speech data. This repository provides the necessary scripts, configurations, and setup instructions to reproduce the experiments discussed in the paper.

Setup

To set up the environment and run the experiments, follow the steps below:

1. Create a Virtual Environment

Before you start, create a Python virtual environment and install the required dependencies.

pip install -r requirements.txt

2. Configure Hugging Face Token

You will need a Hugging Face API token to access certain resources used in this project. Insert your Hugging Face token into the relevant YAML configuration files.

3. Run the Experiments

Once the environment is set up and the configurations are complete, you can run the experiments using the provided script.

sh run.sh

Cite our work

@misc{leduc2024wav2graphframeworksupervisedlearning,
      title={wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech}, 
      author={Khai Le-Duc and Quy-Anh Dang and Tan-Hanh Pham and Truong-Son Hy},
      year={2024},
      eprint={2408.04174},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2408.04174}, 
}