README.md

metadata

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:

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.