https://github.com/dsksd/sden-pytorch
Pytorch Implementation of "Sequential Dialogue Context Modeling for Spoken Language Understanding( https://arxiv.org/abs/1705.03455 )"
https://github.com/dsksd/sden-pytorch
chatbot multi-domain multi-turn nlp nlu task-oriented
Last synced: 3 days ago
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Pytorch Implementation of "Sequential Dialogue Context Modeling for Spoken Language Understanding( https://arxiv.org/abs/1705.03455 )"
- Host: GitHub
- URL: https://github.com/dsksd/sden-pytorch
- Owner: DSKSD
- Created: 2018-04-19T11:20:31.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-07-10T09:18:39.000Z (about 7 years ago)
- Last Synced: 2025-06-20T10:40:01.328Z (4 months ago)
- Topics: chatbot, multi-domain, multi-turn, nlp, nlu, task-oriented
- Language: Python
- Homepage:
- Size: 42.7 MB
- Stars: 34
- Watchers: 4
- Forks: 9
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# SDEN-Pytorch
Pytorch implementation of [Sequential Dialogue Context Modeling for Spoken Language
Understanding](https://arxiv.org/pdf/1705.03455.pdf)
## Requirements
```
pytorch==0.4
nltk==3.5.1
sklearn_crfsuite
```
## Run
```
python3 main.py
```
## Data
I have modified [Stanford Multi-turn dataset](https://nlp.stanford.edu/blog/a-new-multi-turn-multi-domain-task-oriented-dialogue-dataset/) to fit this model. *So it has some noise especially slot tags.*
It consists of three domain, `Weather`, `Schedule`, `Navigate`. I did dialogue recombination for multi-domain dialogue and modified its format to BIO.
### sample
#### Single domain dialogue
```
User : Will it be hot in Inglewood over the next few days?
BOT : It will be warm both Monday and Tuesday in Inglewood.
User : Thank you very much.
BOT : You're welcome. Hope you have a great day.
```
#### Multi domain dialogue
```
User : is it going to be raining this weekend
BOT : What city are you inquiring about?
User : Alhambra please.
BOT : It will be raining on Saturday and hailing on Sunday in Alhambra.
User : Thanks.
BOT : happy to help
User : I need a gas station
BOT : I have one gas station listed. Want more info?
User : What is the address?
BOT : 76 is at 91 El Camino Real.
User : Thank you!
BOT : You're welcome, stay safe.
```
## Devset Result
`Intent Detection : 0.9503091367071216 (Accuracy)`
`Slot Extraction`
| | precision| recall | f1-score | support |
|---------------------|----------|--------|----------|---------|
| B-agenda |0.256 |0.278 |0.267 |36 |
| I-agenda |0.733 |0.407 |0.524 |54 |
| B-date |0.826 |0.836 |0.831 |911 |
| I-date |0.533 |0.885 |0.665 |549 |
| B-distance |0.624 |0.674 |0.648 |487 |
| I-distance |0.424 |0.353 |0.386 |167 |
| B-event |0.813 |0.793 |0.803 |517 |
| I-event |0.637 |0.847 |0.727 |367 |
| B-location |0.718 |0.928 |0.809 |572 |
| I-location |0.384 |0.950 |0.547 |280 |
| B-party |0.298 |0.807 |0.435 |187 |
| I-party |0.471 |0.471 |0.471 |17 |
| B-poi_type |0.790 |0.738 |0.763 |534 |
| I-poi_type |0.528 |0.718 |0.608 |301 |
| B-room |1.000 |0.400 |0.571 |35 |
| I-room |0.683 |0.848 |0.757 |33 |
| B-time |0.496 |0.595 |0.541 |220 |
| I-time |0.129 |0.286 |0.178 |14 |
| B-traffic_info |0.661 |0.527 |0.587 |237 |
| I-traffic_info |0.749 |0.636 |0.688 |272 |
| B-weather_attribute |0.904 |0.877 |0.890 |546 |
| I-weather_attribute |0.954 |0.775 |0.855 |80 |
| avg / total |0.683 |0.775 |0.712 |6416 |