Datasets:
kor_3i4k

Task Categories: text-classification
Languages: ko
Multilinguality: monolingual
Size Categories: 10K<n<100K
Licenses: cc-by-4.0
Language Creators: expert-generated
Annotations Creators: expert-generated
Source Datasets: original
Dataset Preview Go to dataset viewer
label (class label)text (string)
fragment
만화
fragment
이치가
fragment
fragment
그사이
fragment
짜긴
fragment
혜택
fragment
지출
fragment
어젯밤
fragment
승진
fragment
꼬마
fragment
신청
fragment
엄마 꼭 꼭
fragment
어어 그게
fragment
브로셔 보여준다는 게
fragment
김밥
fragment
끝내
fragment
대학
fragment
손잡이
fragment
참여
fragment
fragment
차차
fragment
집안일
fragment
내내 싸들고
fragment
그냥
fragment
구별
fragment
시합
fragment
글자
fragment
비슷한
fragment
의사
fragment
그래
fragment
여군
fragment
골목
fragment
경쟁력
fragment
한층
fragment
도대체
fragment
희곡
fragment
이러고
fragment
없을
fragment
반죽
fragment
자리
fragment
지금 도착
fragment
볶음밥
fragment
그거
fragment
참석자
fragment
젓가락
fragment
소위
fragment
fragment
몇몇
fragment
얘길
fragment
너무
fragment
발음
fragment
fragment
fragment
아나운서
fragment
fragment
걸음
fragment
단둘이
fragment
fragment
의사
fragment
실수
fragment
치아
fragment
개미
fragment
뿌듯
fragment
처음
fragment
누구
fragment
영화배우
fragment
여친
fragment
버터
fragment
비참한
fragment
우리가
fragment
오로지
fragment
fragment
얘길
fragment
실내
fragment
단순히
fragment
과제
fragment
좌석
fragment
여럿
fragment
주변
fragment
한번
fragment
뭐야 그거
fragment
나쁜 눔이
fragment
최소한
fragment
형수
fragment
방면
fragment
영역
fragment
fragment
fragment
그만
fragment
국제선
fragment
안녕
fragment
과외
fragment
fragment
유리창
fragment
퇴직금
fragment
위아래
fragment
과자
fragment
아까
fragment
여기
fragment
금메달

Dataset Card for 3i4K

Dataset Summary

The 3i4K dataset is a set of frequently used Korean words (corpus provided by the Seoul National University Speech Language Processing Lab) and manually created questions/commands containing short utterances. The goal is to identify the speaker intention of a spoken utterance based on its transcript, and whether in some cases, requires using auxiliary acoustic features. The classification system decides whether the utterance is a fragment, statement, question, command, rhetorical question, rhetorical command, or an intonation-dependent utterance. This is important because in head-final languages like Korean, the level of the intonation plays a significant role in identifying the speaker's intention.

Supported Tasks and Leaderboards

  • intent-classification: The dataset can be trained with a CNN or BiLISTM-Att to identify the intent of a spoken utterance in Korean and the performance can be measured by its F1 score.

Languages

The text in the dataset is in Korean and the associated is BCP-47 code is ko-KR.

Dataset Structure

Data Instances

An example data instance contains a short utterance and it's label:

{
  "label": 3,
  "text": "선수잖아 이 케이스 저 케이스 많을 거 아냐 선배라고 뭐 하나 인생에 도움도 안주는데 내가 이렇게 진지하게 나올 때 제대로 한번 조언 좀 해줘보지"
}

Data Fields

  • label: determines the intention of the utterance and can be one of fragment (0), statement (1), question (2), command (3), rhetorical question (4), rhetorical command (5) and intonation-depedent utterance (6).
  • text: the text in Korean about common topics like housework, weather, transportation, etc.

Data Splits

The data is split into a training set comrpised of 55134 examples and a test set of 6121 examples.

Dataset Creation

Curation Rationale

For head-final languages like Korean, intonation can be a determining factor in identifying the speaker's intention. The purpose of this dataset is to to determine whether an utterance is a fragment, statement, question, command, or a rhetorical question/command using the intonation-depedency from the head-finality. This is expected to improve language understanding of spoken Korean utterances and can be beneficial for speech-to-text applications.

Source Data

Initial Data Collection and Normalization

The corpus was provided by Seoul National University Speech Language Processing Lab, a set of frequently used words from the National Institute of Korean Language and manually created commands and questions. The utterances cover topics like weather, transportation and stocks. 20k lines were randomly selected.

Who are the source language producers?

Korean speakers produced the commands and questions.

Annotations

Annotation process

Utterances were classified into seven categories. They were provided clear instructions on the annotation guidelines (see here for the guidelines) and the resulting inter-annotator agreement was 0.85 and the final decision was done by majority voting.

Who are the annotators?

The annotation was completed by three Seoul Korean L1 speakers.

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

[More Information Needed]

Additional Information

Dataset Curators

The dataset is curated by Won Ik Cho, Hyeon Seung Lee, Ji Won Yoon, Seok Min Kim and Nam Soo Kim.

Licensing Information

The dataset is licensed under the CC BY-SA-4.0.

Citation Information

@article{cho2018speech,
    title={Speech Intention Understanding in a Head-final Language: A Disambiguation Utilizing Intonation-dependency},
    author={Cho, Won Ik and Lee, Hyeon Seung and Yoon, Ji Won and Kim, Seok Min and Kim, Nam Soo},
    journal={arXiv preprint arXiv:1811.04231},
    year={2018}
}

Contributions

Thanks to @stevhliu for adding this dataset.

Models trained or fine-tuned on kor_3i4k