Update README.md

README.md

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----
-license: cc-by-nc-4.0
-dataset_info:
-  features:
-  - name: swahili
-    dtype: string
-  - name: machine_translated_english
-    dtype: string
-  - name: validated_english
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 6491320
-    num_examples: 29230
-  download_size: 3885224
-  dataset_size: 6491320
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+# Swahili–English Extension of Kidaw’ida, Kalenjin and Dholuo Parallel Corpus
+
+## Dataset Description
+
+This dataset is an extension of the parallel corpora introduced in **[Building Low-Resource African Language Corpora: A Case Study of Kidaw’ida, Kalenjin and Dholuo](https://arxiv.org/html/2501.11003v1)** by:
+- Ambrose N. Ambogho
+- Quin Awuor
+- Andrew Kipkebut
+- Lilian Wanzare
+- Vivian Oloo
+
+The original dataset provides **Swahili–[Kidaw’ida/Kalenjin/Dholuo]** parallel sentence pairs. English was not included in the original corpus.
+
+### Our Contribution
+
+We extend the original dataset by:
+
+1. Using Machine Translation (MT) to translate the Swahili side of the dataset into English.
+2. Conducting human validation of the English translations with language speakers.
+3. Releasing both:
+   - `machine_translated_english`
+   - `validated_english`
+
+This results in a new **Swahili–English** aligned dataset, while preserving the integrity of the original Swahili source sentences.
+
+**Please note that this data is still experimental and the validation may still be reviewed/improved.**
+
+---
+
+## Dataset Structure
+
+### Features
+
+- `swahili` (string): Original Swahili sentence from the source dataset  
+- `machine_translated_english` (string): Raw MT output from Swahili → English  
+- `validated_english` (string): Human-reviewed and corrected English translation  
+
+### Splits
+
+- **train**
+  - Examples: 29,230  
+  - Dataset size: 6,491,320 bytes  
+
+---
+
+## Motivation
+
+English parallel data significantly improves:
+
+- Cross-lingual transfer learning  
+- Multilingual foundation model training  
+- Evaluation benchmarks  
+- Accessibility for global research communities  
+
+By adding validated English translations, we increase interoperability of these low-resource African languages with broader NLP ecosystems.
+
+---
+
+## Data Citation
+
+If you use this dataset, please cite both:
+1. The original authors.  
+2. This extended English translation version.  
+
+---
+
+## License
+
+This dataset follows the original dataset license:
+
+**CC-BY-NC-4.0**
+
+Please review the original paper and dataset terms before commercial use.