sonlam1102/vlogqa

Dataset Card for Dataset Name

VlogQA: Question-answering based on the transcript from VLOG Videos in Vietnamese Language about travel and food.

Dataset Details

VlogQA consists of 10,076 question-answer pairs based on 1,230 transcript documents sourced from YouTube

You need to sign the agreement and send to the author via the email in "Dataset Contact" to access to the dataset. The agreement from can be found at: https://github.com/sonlam1102/vlogqa/blob/main/VlogQA_User_Agreement.pdf

Uses

from datasets import load_dataset
load_dataset("sonlam1102/vlogqa")

License

The user of VlogQA developed by the NLP@UIT research group must respect the following terms and conditions:

• The dataset is only used for non-profit research for natural language processing and education.
• The dataset is not allowed to be used in commercial systems.
• Do not redistribute the dataset. This dataset may be modified or improved to serve a research purpose better, but the edited dataset may not be distributed.
• Summaries, analyses, and interpretations of the properties of the dataset may be derived and published, provided it is not possible to reconstruct the information from these summaries.
• Published research works that use the dataset must cite the following paper: Thinh Ngo, Khoa Dang, Son Luu, Kiet Nguyen, and Ngan Nguyen. 2024. VlogQA: Task, Dataset, and Baseline Models for Vietnamese Spoken-Based Machine Reading Comprehension. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1310–1324, St. Julian’s, Malta. Association for Computational Linguistics.

Publication

@inproceedings{ngo-etal-2024-vlogqa,
    title = "{V}log{QA}: Task, Dataset, and Baseline Models for {V}ietnamese Spoken-Based Machine Reading Comprehension",
    author = "Ngo, Thinh  and
      Dang, Khoa  and
      Luu, Son  and
      Nguyen, Kiet  and
      Nguyen, Ngan",
    editor = "Graham, Yvette  and
      Purver, Matthew",
    booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2024",
    address = "St. Julian{'}s, Malta",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.eacl-long.79",
    pages = "1310--1324",
    abstract = "This paper presents the development process of a Vietnamese spoken language corpus for machine reading comprehension (MRC) tasks and provides insights into the challenges and opportunities associated with using real-world data for machine reading comprehension tasks. The existing MRC corpora in Vietnamese mainly focus on formal written documents such as Wikipedia articles, online newspapers, or textbooks. In contrast, the VlogQA consists of 10,076 question-answer pairs based on 1,230 transcript documents sourced from YouTube {--} an extensive source of user-uploaded content, covering the topics of food and travel. By capturing the spoken language of native Vietnamese speakers in natural settings, an obscure corner overlooked in Vietnamese research, the corpus provides a valuable resource for future research in reading comprehension tasks for the Vietnamese language. Regarding performance evaluation, our deep-learning models achieved the highest F1 score of 75.34{\%} on the test set, indicating significant progress in machine reading comprehension for Vietnamese spoken language data. In terms of EM, the highest score we accomplished is 53.97{\%}, which reflects the challenge in processing spoken-based content and highlights the need for further improvement.",
}

Dataset Contact

Email: sonlt@uit.edu.vn (Alternative: son.lt1103@gmail.com)