---
configs:
- config_name: default
  data_files:
  - split: en_in
    path: data/en_in-*
  - split: en_ng
    path: data/en_ng-*
  - split: en_us
    path: data/en_us-*
- config_name: en_in
  data_files:
  - split: train
    path: en_in/train-*
- config_name: en_ng
  data_files:
  - split: train
    path: en_ng/train-*
- config_name: en_us
  data_files:
  - split: train
    path: en_us/train-*
dataset_info:
- config_name: default
  features:
  - name: transcript
    dtype: string
  - name: correct_word
    dtype: string
  - name: distractors
    dtype: string
  - name: win
    dtype: string
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: en_in
    num_bytes: 445911
    num_examples: 447
  - name: en_ng
    num_bytes: 485626
    num_examples: 471
  - name: en_us
    num_bytes: 465533
    num_examples: 478
  download_size: 524698
  dataset_size: 1397070
- config_name: en_in
  features:
  - name: transcript
    dtype: string
  - name: correct_word
    dtype: string
  - name: distractors
    dtype: string
  - name: win
    dtype: string
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 445911
    num_examples: 447
  download_size: 158201
  dataset_size: 445911
- config_name: en_ng
  features:
  - name: transcript
    dtype: string
  - name: correct_word
    dtype: string
  - name: distractors
    dtype: string
  - name: win
    dtype: string
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 485626
    num_examples: 471
  download_size: 187583
  dataset_size: 485626
- config_name: en_us
  features:
  - name: transcript
    dtype: string
  - name: correct_word
    dtype: string
  - name: distractors
    dtype: string
  - name: win
    dtype: string
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 465533
    num_examples: 478
  download_size: 178914
  dataset_size: 465533
---
## Original Attribution

MD3-EN: The Multi-Dialect Dataset of Dialogues
- Authors: Jacob Eisenstein (jeisenstein@google.com), Clara Rivera, Vinodkumar Prabhakaran, Jon Clark, Dora Demszky, Sunny Mak, Ravi Rajakumar, David Elworthy, Landis Baker, Devyani Sharma
- Paper: https://arxiv.org/abs/2305.11355, published at InterSpeech 2023
- License: CC BY-SA 4.0

## Dataset Description

The MD3 Taboo Game dataset consists of transcripts of two people playing the Taboo game, where one person tries to get the other to guess a secret word without saying certain distractor words.

The dataset includes:
- Transcripts from 3 English dialects: Indian English (en_in), Nigerian English (en_ng), and American English (en_us)
- The correct word to be guessed in each game
- Distractor words that cannot be used during the game

## Dataset Structure

The dataset is organized into three splits by dialect:
- `en_in`: Indian English
- `en_ng`: Nigerian English
- `en_us`: American English

Each split contains the following fields:
- `id`: Unique identifier for the dialogue
- `transcript`: The dialogue transcript
- `correct_word`: The target word to be guessed
- `distractors`: List of words that cannot be used during the game

## Usage

This dataset can be used to evaluate language models on their ability to understand contextual clues and infer missing information, similar to how a human would play the Taboo game.

Example usage:
```python
from datasets import load_dataset

dataset = load_dataset("REPO_NAME_HERE")
example = dataset["en_us"][0]
print(f"Transcript: {example['transcript']}")
print(f"Correct word: {example['correct_word']}")
print(f"Distractors: {example['distractors']}")
```

## Citation

If you use this dataset, please cite the original MD3 paper:

```
@inproceedings{eisenstein2023md3,
  title={MD3: The Multi-Dialect Dataset of Dialogues},
  author={Eisenstein, Jacob and Rivera, Clara and Prabhakaran, Vinodkumar and Clark, Jon and Demszky, Dora and Mak, Sunny and Rajakumar, Ravi and Elworthy, David and Baker, Landis and Sharma, Devyani},
  booktitle={Proceedings of INTERSPEECH},
  year={2023}
}
```

## License

This re-release of the dataset is bound by the original MD3 corpus CC BY-SA 4.0 license.