|
|
--- |
|
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configs: |
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- config_name: default |
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data_files: |
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- split: en_in |
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path: data/en_in-* |
|
|
- split: en_ng |
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|
path: data/en_ng-* |
|
|
- split: en_us |
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path: data/en_us-* |
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|
- config_name: en_in |
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|
data_files: |
|
|
- split: train |
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|
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. |