README.md

---
license: cc-by-4.0
language: 
- ind
- jav
- khm
- zlm
- mya
- tha
- tgl
- vie
pretty_name: Massive
task_categories: 
- intent-classification
- slot-filling
tags: 
- intent-classification
- slot-filling
---

MASSIVE dataset—Multilingual Amazon Slu resource package (SLURP) for Slot-filling, Intent classification, and
Virtual assistant Evaluation. MASSIVE contains 1M realistic, parallel, labeled virtual assistant utterances
spanning 18 domains, 60 intents, and 55 slots. MASSIVE was created by tasking professional translators to
localize the English-only SLURP dataset into 50 typologically diverse languages, including 8 native languages
and 2 other languages mostly spoken in Southeast Asia.


## Languages

ind, jav, khm, zlm, mya, tha, tgl, vie

## Supported Tasks

Intent Classification, Slot Filling

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/massive", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("massive", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("massive"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
```

More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).


## Dataset Homepage

[https://github.com/alexa/massive](https://github.com/alexa/massive)

## Dataset Version

Source: 1.1.0. SEACrowd: 2024.06.20.

## Dataset License

Creative Commons Attribution 4.0 (cc-by-4.0)

## Citation

If you are using the **Massive** dataloader in your work, please cite the following:
```
@misc{fitzgerald2022massive,
      title={MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages},
      author={Jack FitzGerald and Christopher Hench and Charith Peris and Scott Mackie and Kay Rottmann and Ana Sanchez and Aaron
      Nash and Liam Urbach and Vishesh Kakarala and Richa Singh and Swetha Ranganath and Laurie Crist and Misha Britan and Wouter
      Leeuwis and Gokhan Tur and Prem Natarajan},
      year={2022},
      eprint={2204.08582},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
@inproceedings{bastianelli-etal-2020-slurp,
    title = "{SLURP}: A Spoken Language Understanding Resource Package",
    author = "Bastianelli, Emanuele  and
      Vanzo, Andrea  and
      Swietojanski, Pawel  and
      Rieser, Verena",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.emnlp-main.588",
    doi = "10.18653/v1/2020.emnlp-main.588",
    pages = "7252--7262",
    abstract = "Spoken Language Understanding infers semantic meaning directly from audio data, and thus promises to
    reduce error propagation and misunderstandings in end-user applications. However, publicly available SLU resources are limited.
    In this paper, we release SLURP, a new SLU package containing the following: (1) A new challenging dataset in English spanning
    18 domains, which is substantially bigger and linguistically more diverse than existing datasets; (2) Competitive baselines
    based on state-of-the-art NLU and ASR systems; (3) A new transparent metric for entity labelling which enables a detailed error
    analysis for identifying potential areas of improvement. SLURP is available at https://github.com/pswietojanski/slurp."
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}

```