| --- |
| language: |
| - my |
| license: cc-by-4.0 |
| size_categories: |
| - 1K<n<10K |
| task_categories: |
| - text-generation |
| - translation |
| - summarization |
| tags: |
| - myanmar |
| - burmese |
| - formal-to-informal |
| - written-to-spoken |
| - nlp |
| - mwspc |
| dataset_info: |
| features: |
| - name: written_style |
| dtype: string |
| - name: spoken_style |
| dtype: string |
| splits: |
| - name: train |
| num_examples: 5555 |
| pretty_name: Myanmar Written-Spoken Parallel Corpus (MWSPC) |
| --- |
| |
| # Myanmar Written-Spoken Parallel Corpus (MWSPC) |
|
|
| ## Dataset Description |
|
|
| Myanmar Written-Spoken Parallel Corpus (MWSPC) is a high-quality open-source dataset designed to bridge the gap between formal written Burmese and daily spoken Burmese. This dataset is crucial for building natural-sounding AI models that understand the linguistic nuances of the Myanmar language. |
|
|
| - **Curated by:** [Khant Sint Heinn (Kalix Louis)](https://huggingface.co/kalixlouiis) |
| - **Organization:** [DatarrX | ဒေတာ-အက်စ်](https://huggingface.co/DatarrX) |
| - **Language:** Burmese (Myanmar) |
| - **License:** Creative Commons Attribution 4.0 International (CC-BY-4.0) |
|
|
| ### What is Written vs. Spoken Burmese? |
|
|
| Burmese is a **diglossic** language, meaning there is a significant difference between the formal literary style and the informal colloquial style. |
|
|
| - **Written Style (Literary/Formal):** Used in news, textbooks, legal documents, and official speeches. It uses specific grammatical markers like "သည်" (thi), "၏" (ei), and "၍" (yway). |
| - **Spoken Style (Colloquial/Informal):** Used in daily conversations, social media, and fiction dialogue. It uses markers like "တယ်" (tal), "ရဲ့" (yae), and "ပြီး" (pyee). |
|
|
| AI models trained only on formal texts often sound unnatural to native speakers. **MWSPC** provides direct mapping between these two styles to enable "Style Transfer" and "Natural Language Understanding." |
|
|
| ## Dataset Structure |
|
|
| The dataset consists of **5,555 rows** of parallel text pairs. |
|
|
| | Field | Description | |
| |---|---| |
| | `written_style` | Formal/Literary version of the sentence (Formal Burmese) | |
| | `spoken_style` | Informal/Colloquial version of the sentence (Spoken Burmese) | |
|
|
| ### Data Quality |
| Every row in this dataset has been strictly filtered to ensure **100% uniqueness**. All duplicate entries have been removed, resulting in **5,555 high-quality, unique parallel text pairs**. |
|
|
| ### Development History |
| This dataset was built by aggregating and refining: |
| 1. **[kalixlouiis/myanmar-written-spoken-text-pairs](https://huggingface.co/datasets/kalixlouiis/myanmar-written-spoken-text-pairs)** (1,643 rows). |
| 2. **Additional Curated Data:** 3,912 new rows added to ensure high diversity and accuracy. |
|
|
| ## Uses |
|
|
| ### Direct Use |
| - **Style Transfer:** Converting formal news or documents into casual spoken language for chatbots. |
| - **Machine Translation:** Improving the fluency of translations from English to Burmese. |
| - **Preprocessing:** Normalizing social media text into formal Burmese for downstream NLP tasks. |
|
|
| ## Dataset Creation |
|
|
| ### Curation Rationale |
| In the current AI era, most Myanmar datasets are scraped from news sites, which are heavily biased towards the "Written Style." This creates a lack of data for "Spoken Style" applications. MWSPC was created to empower the Burmese AI ecosystem with a data-rich foundation for next-generation innovation. |
|
|
| ## Bias, Risks, and Limitations |
|
|
| While the dataset covers various patterns, Burmese is a dialect-rich language. This dataset primarily focuses on the standard dialect (Yangon/Mandalay). Users should be aware that regional slang or extremely casual internet lingo may not be fully represented. |
|
|
| ## Citation |
|
|
| If you use this dataset in your research or project, please cite it as follows: |
|
|
| **APA:** |
| Khant Sint Heinn, (2026). Myanmar Written-Spoken Parallel Corpus (MWSPC). DatarrX Foundation. Retrieved from [https://huggingface.co/datasets/DatarrX/Myanmar-Written-Spoken-Parallel-Corpus] |
|
|
| **BibTeX:** |
| ```bibtex |
| @dataset{mwspc, |
| author = {Khant Sint Heinn (Kalix Louis)}, |
| title = {Myanmar Written-Spoken Parallel Corpus (MWSPC)}, |
| year = {2026}, |
| publisher = {Hugging Face}, |
| organization = {DatarrX}, |
| url = {https://huggingface.co/datasets/DatarrX/MWSPC} |
| } |
| ``` |
|
|
| --- |
|
|
| ## About the Author |
|
|
| **Khant Sint Heinn**, working under the name **Kalix Louis**, is a **Machine Learning Engineer focused on Natural Language Processing (NLP), data foundations, and open-source AI development**. His work is centered on improving support for the Burmese (Myanmar) language in modern AI systems by building high-quality datasets, practical tools, and scalable infrastructure for language technology. |
|
|
| He is currently the **Lead Developer at DatarrX**, where he develops data pipelines, manages large-scale data collection workflows, and helps create open-source resources for researchers, developers, and organizations. His experience includes data engineering, web scripting, dataset curation, and building systems that support real-world machine learning applications. |
|
|
| Khant Sint Heinn is especially interested in advancing low-resource languages and making AI more accessible to underrepresented communities. Through his open-source contributions, he works to strengthen the Burmese (Myanmar) tech ecosystem and provide reliable building blocks for future language models, search systems, and intelligent applications. |
|
|
| His goal is simple: to turn limited language resources into practical opportunities through clean data, useful tools, and community-driven innovation. |
|
|
| **Connect with the Author:** |
| [GitHub](https://github.com/kalixlouiis) | [Hugging Face](https://huggingface.co/kalixlouiis) | [Kaggle](https://www.kaggle.com/organizations/kalixlouiis) |
