NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages
Natural language processing (NLP) has a significant impact on society via technologies such as machine translation and search engines. Despite its success, NLP technology is only widely available for high-resource languages such as English and Chinese, while it remains inaccessible to many languages due to the unavailability of data resources and benchmarks. In this work, we focus on developing resources for languages in Indonesia. Despite being the second most linguistically diverse country, most languages in Indonesia are categorized as endangered and some are even extinct. We develop the first-ever parallel resource for 10 low-resource languages in Indonesia. Our resource includes datasets, a multi-task benchmark, and lexicons, as well as a parallel Indonesian-English dataset. We provide extensive analyses and describe the challenges when creating such resources. We hope that our work can spark NLP research on Indonesian and other underrepresented languages.
Code (2)
Tasks
Machine TranslationTranslationSimilar Papers 제목 키워드 기반
Improving Indonesian Text Classification Using Multilingual Language Model
Compared to English, the amount of labeled data for Indonesian text classification tasks is very small. Recently developed multilingual language models have shown its ability to create multilingual representations effect…
ClassificationGeneral ClassificationLanguage ModelingLanguage Modelling+4Fine-tuning Pretrained Multilingual BERT Model for Indonesian Aspect-based Sentiment Analysis
Although previous research on Aspect-based Sentiment Analysis (ABSA) for Indonesian reviews in hotel domain has been conducted using CNN and XGBoost, its model did not generalize well in test data and high number of OOV …
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Sentiment AnalysisBERT Fine-Tuning for Sentiment Analysis on Indonesian Mobile Apps Reviews
User reviews have an essential role in the success of the developed mobile apps. User reviews in the textual form are unstructured data, creating a very high complexity when processed for sentiment analysis. Previous app…
Sentiment AnalysisTransfer LearningidT5: Indonesian Version of Multilingual T5 Transformer
Indonesian language is spoken by almost 200 million people and is the 10th most spoken language in the world, but it is under-represented in NLP (Natural Language Processing) research. A sparsity of language resources ha…
Question AnsweringQuestion GenerationQuestion-GenerationSentiment AnalysisConstructing and Expanding Low-Resource and Underrepresented Parallel Datasets for Indonesian Local Languages
In Indonesia, local languages play an integral role in the culture. However, the available Indonesian language resources still fall into the category of limited data in the Natural Language Processing (NLP) field. This i…
Translation