# Prompt-based methods for Dialog State Tracking  
  
Repository for my master thesis at the University of Stuttgart (IMS).  
  
Refer to this thesis [proposal](proposal/proposal_submission_1st.pdf) document for detailed explanation about thesis experiments.  
    
## Dataset
MultiWOZ 2.1 [dataset](https://github.com/budzianowski/multiwoz/blob/master/data/MultiWOZ_2.1.zip) is used for training and evaluation of the baseline/prompt-based methods. MultiWOZ is a fully-labeled dataset with a collection of human-human written conversations spanning over multiple domains and topics. Only single-domain dialogues are used in this setup for training and testing. Each dialogue contains multiple turns and may also contain a sub-domain *booking*. Five domains - *Hotel, Train, Restaurant, Attraction, Taxi* are used in the experiments and excluded the other two domains as they only appear in the training set. Under few-shot settings, only a portion of the training data is utilized to measure the performance of the DST task in a low-resource scenario. Dialogues are randomly picked for each domain. The below table contains some statistics of the dataset and data splits for the few-shot experiments.

| Data Split | # Dialogues | # Total Turns |
|--|:--:|:--:|
| 50-dpd | 250 | 1114 |
| 100-dpd | 500 | 2292 |
| 125-dpd | 625 | 2831 |
| 250-dpd | 1125 | 5187 |
| valid | 190 | 900 |
| test | 193 | 894 |

In the above table, term "*dpd*" refers to "*dialogues per domain*". For example, *50-dpd* means *50 dialogues per each domain*.