Datasets:
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 Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: Github
- Repository: Github
- Paper: Rikters et al., 2019
- Leaderboard:
- Point of Contact: Matīss Rikters
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:
- selecting business scenes,
- writing monolingual conversation scenarios according to the selected scenes, and
- 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.