Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization
DDAMS
This is the pytorch code for our IJCAI 2021 paper Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization [Arxiv Preprint].
Requirements
- We use Conda python 3.7 and strongly recommend that you create a new environment:
conda create -n ddams python=3.7. - Run the following command:
pip install -r requirements.txt.
Data
You can download data here, put the data under the project dir DDAMS/data/xxx.
- data/ami
- data/ami/ami: preprocessed meeting data
- data/ami/ami_qg: pseudo summarization data.
- data/ami/ami_reference: golden reference for test file.
- data/icsi
- data/icsi/icsi: preprocessed meeting data
- data/icsi/icsi_qg: pseudo summarization data.
- data/icsi/icsi_reference: golden reference for test file.
- data/glove: pre-trained word embedding
glove.6B.300d.txt.
Reproduce Results
You can follow the following steps to reproduce the best results in our paper.
download checkpoints