The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets library). If this is not possible, please
open a discussion
for direct help.
parallel_id_nyo
Dataset that contains Indonesian - Lampung language pairs.
The original data should contains 3000 rows, unfortunately,
not all of the instances in the original data is aligned perfectly.
Thus, this data only have the aligned ones, which only contain 1727 pairs.
Dataset Usage
Run pip install nusacrowd before loading the dataset through HuggingFace's load_dataset.
Citation
@article{Abidin_2021,
doi = {10.1088/1742-6596/1751/1/012036},
url = {https://dx.doi.org/10.1088/1742-6596/1751/1/012036},
year = {2021},
month = {jan},
publisher = {IOP Publishing},
volume = {1751},
number = {1},
pages = {012036},
author = {Z Abidin and Permata and I Ahmad and Rusliyawati},
title = {Effect of mono corpus quantity on statistical machine translation
Indonesian - Lampung dialect of nyo},
journal = {Journal of Physics: Conference Series},
abstract = {Lampung Province is located on the island of Sumatera. For the
immigrants in Lampung, they have difficulty in
communicating with the indigenous people of Lampung. As an alternative, both
immigrants and the indigenous people of Lampung speak Indonesian.
This research aims to build a language model from Indonesian language and a
translation model from the Lampung language dialect of nyo, both models will
be combined in a Moses decoder.
This research focuses on observing the effect of adding mono corpus to the
experimental statistical machine translation of
Indonesian - Lampung dialect of nyo.
This research uses 3000 pair parallel corpus in Indonesia language and
Lampung language dialect of nyo as source language
and uses 3000 mono corpus sentences in Lampung language
dialect of nyo as target language. The results showed that the accuracy
value in bilingual evalution under-study score when using 1000 sentences,
2000 sentences, 3000 sentences mono corpus
show the accuracy value of the bilingual evaluation under-study,
respectively, namely 40.97 %, 41.80 % and 45.26 %.}
}
License
Unknown
Homepage
https://drive.google.com/drive/folders/1oNpybrq5OJ_4Ne0HS5w9eHqnZlZASpmC?usp=sharing
NusaCatalogue
For easy indexing and metadata: https://indonlp.github.io/nusa-catalogue
- Downloads last month
- 0