bsd_ja_en / README.md
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metadata
annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
language:
  - en
  - ja
license:
  - cc-by-nc-sa-4.0
multilinguality:
  - translation
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - translation
task_ids: []
paperswithcode_id: business-scene-dialogue
pretty_name: Business Scene Dialogue
tags:
  - business-conversations-translation
dataset_info:
  features:
    - name: id
      dtype: string
    - name: tag
      dtype: string
    - name: title
      dtype: string
    - name: original_language
      dtype: string
    - name: 'no'
      dtype: int32
    - name: en_speaker
      dtype: string
    - name: ja_speaker
      dtype: string
    - name: en_sentence
      dtype: string
    - name: ja_sentence
      dtype: string
  splits:
    - name: train
      num_bytes: 4778291
      num_examples: 20000
    - name: test
      num_bytes: 492986
      num_examples: 2120
    - name: validation
      num_bytes: 477935
      num_examples: 2051
  download_size: 1843443
  dataset_size: 5749212
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: validation
        path: data/validation-*

Dataset Card for Business Scene Dialogue

Table of Contents

Dataset Description

Dataset Summary

This is the Business Scene Dialogue (BSD) dataset, a Japanese-English parallel corpus containing written conversations in various business scenarios.

The dataset was constructed in 3 steps:

  1. selecting business scenes,
  2. writing monolingual conversation scenarios according to the selected scenes, and
  3. translating the scenarios into the other language.

Half of the monolingual scenarios were written in Japanese and the other half were written in English.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

English, Japanese.

Dataset Structure

Data Instances

Each instance contains a conversation identifier, a sentence number that indicates its position within the conversation, speaker name in English and Japanese, text in English and Japanese, original language, scene of the scenario (tag), and title of the scenario (title).

        {
      "id": "190315_E004_13",
            "no": 14,
            "speaker": "Mr. Sam Lee",
            "ja_speaker": "サム リーさん",
            "en_sentence": "Would you guys consider a different scheme?",
            "ja_sentence": "別の事業案も考慮されますか?",
            "original_language": "en",
            "tag": "phone call",
            "title": "Phone: Review spec and scheme"
        }

Data Fields

  • id: dialogue identifier
  • no: sentence pair number within a dialogue
  • en_speaker: speaker name in English
  • ja_speaker: speaker name in Japanese
  • en_sentence: sentence in English
  • ja_sentence: sentence in Japanese
  • original_language: language in which monolingual scenario was written
  • tag: scenario
  • title: scenario title

Data Splits

  • There are a total of 24171 sentences / 808 business scenarios.
  • Train: 20000 sentences / 670 scenarios
  • Dev: 2051 sentences / 69 scenarios
  • Test: 2120 sentences / 69 scenarios

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

Dataset provided for research purposes only. Please check dataset license for additional information.

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

This dataset was released under the Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license.

Citation Information

@inproceedings{rikters-etal-2019-designing,
    title = "Designing the Business Conversation Corpus",
    author = "Rikters, Mat{\=\i}ss  and
      Ri, Ryokan  and
      Li, Tong  and
      Nakazawa, Toshiaki",
    booktitle = "Proceedings of the 6th Workshop on Asian Translation",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-5204",
    doi = "10.18653/v1/D19-5204",
    pages = "54--61"
}

Contributions

Thanks to @j-chim for adding this dataset.