Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding
This repository contains the official PyTorch
implementation of the paper:
Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding. Xiao Xu*, Libo Qin*, Kaiji Chen, Guoxing Wu, Linlin Li, Wanxiang Che. AAAI 2022. [Paper(Arxiv)] [Paper]
If you use any source codes or the datasets included in this toolkit in your work, please cite the following paper. The bibtex are listed below:
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In the following, we will guide you how to use this repository step by step.
Workflow
Architecture
Results
Preparation
Our code is based on the following packages:
- numpy==1.19.5
- tqdm==4.50.2
- pytorch==1.7.0
- python==3.7.3
- cudatoolkit==11.0.3
- transformers==4.1.1
We highly suggest you using Anaconda to manage your python environment.
We download the chinese pretrained model checkpoints from the following links:
How to Run it
The script train.py acts as a main function to the project, you can run the experiments by the following commands.
# LSTM w/o Profile on TITAN Xp
python train.py -g -fs -es -uf -bs 8 -lr 0.0006
# LSTM w/ Profile on TITAN Xp
python train.py -g -fs -es -uf -ui -bs 8 -lr 0.0004
# BERT w/o Profile on Tesla V100s PCIE 32GB
python train.py -g -fs -es -uf -up -mt XLNet -bs 8 -lr 0.001 -blr 4e-05
# BERT w/ Profile on Tesla V100 PCIE 32GB
python train.py -g -fs -es -uf -up -ui -mt ELECTRA -bs 8 -lr 0.0008 -blr 4e-05
If you have any question, please issue the project or email me or lbqin, and we will reply you soon.
Acknowledgement
- We are highly grateful for the public code of Stack-Propagation!
A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding. Libo Qin,Wanxiang Che, Yangming Li, Haoyang Wen and Ting Liu. (EMNLP 2019). Long paper. [pdf] [code]
- We are highly grateful for the open-source knowledge graph!