Update README.md

README.md

@@ -1,55 +1,57 @@
----
-license: cc0-1.0
-task_categories:
-- text-classification
-- text-generation
-- text-to-speech
-language:
-- my
-pretty_name: my_written_corpus
-size_categories:
-- 10M<n<100M
-tags:
-- tts,
-- asr,
-- myanmar,
-- burmese,
-- corpus
----
+---
+license: cc0-1.0
+task_categories:
+- text-classification
+- text-generation
+- text-to-speech
+language:
+- my
+pretty_name: my_written_corpus
+size_categories:
+- 10M<n<100M
+tags:
+- nlp
+- chatgpt
+- tts
+- corpus,
+- language,
+---
 
 # Myanmar Written Corpus
 
-The **Myanmar Written Corpus** is a large collection of high-quality written Myanmar text, designed to support various NLP tasks such as text-to-speech (TTS), automatic speech recognition (ASR), translation, text generation, and more. This dataset serves as a foundational resource for developing Myanmar language technologies.
+The **Myanmar Written Corpus** is a comprehensive collection of high-quality written Myanmar text, designed to address the lack of large-scale, openly accessible resources for Myanmar Natural Language Processing (NLP). It is tailored to support various tasks such as text-to-speech (TTS), automatic speech recognition (ASR), translation, text generation, and more.
+
+This dataset serves as a critical resource for researchers and developers aiming to advance Myanmar language technologies.
 
 ## Dataset Overview
 
 - **Language**: Myanmar
 - **Format**: Parquet
-- **Size**: 10 million sentences.
+- **Size**: 10 million sentences
 - **License**: [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/)
-- **Intended Use**: Research and development in Myanmar language NLP tasks.
+- **Purpose**: To support research and development in Myanmar NLP tasks.
 
 ## Features
 
-| Field Name       | Description                                           |
-|-------------------|-------------------------------------------------------|
-| `sentence_id`     | Unique ID for each sentence.                         |
-| `text`            | The written Myanmar text.                            |
-| `string_length`   | Character count of the text.                         |
-| `length_category` | Length category of the text (`<100`, `<200`, etc.). |
+| Field Name       | Description                                                               |
+|-------------------|---------------------------------------------------------------------------|
+| `sentence_id`     | A unique numeric ID for each sentence.                                   |
+| `text`            | The original written Myanmar sentence.                                  |
+| `string_length`   | The number of characters in the sentence.                               |
+| `length_category` | Categorization of the sentence length (e.g., `<100`, `<200`, etc.).      |
 
 ## Dataset Statistics
 
 - **Total Sentences**: 10 million.
 - **Character Length Ranges**:
-  - `<100`: Count of sentences (to be added after analysis).
-  - `<200`: Count of sentences (to be added after analysis).
-  - `<300`: Count of sentences (to be added after analysis).
-  - ... (Add other ranges as needed).
+  - `<100`: To be analyzed.
+  - `<200`: To be analyzed.
+  - `<300`: To be analyzed.
+  - ... (Expand as needed).
 
 ## Example Usage
 
-The dataset can be used with the `datasets` library from Hugging Face:
+The dataset can be loaded using the `datasets` library from Hugging Face:
 
 ```python
 from datasets import load_dataset
@@ -57,30 +59,35 @@ from datasets import load_dataset
 # Load the dataset
 dataset = load_dataset("freococo/myanmar-written-corpus")
 
-# Example: Print the first 5 sentences
-print(dataset["train"][:5])
+# Access features
+print(dataset["train"][0])  # Print the first example
+print(dataset["train"][:5])  # Print the first 5 examples
+
+# Access specific columns
+texts = dataset["train"]["text"]  # Extract all sentences
+lengths = dataset["train"]["string_length"]  # Extract string lengths
 ```
 
 ## Applications
 
 This dataset is suitable for:
-	•	Training and evaluating NLP models for the Myanmar language.
-	•	Text-to-Speech (TTS) synthesis.
-	•	Automatic Speech Recognition (ASR).
-	•	Machine Translation (MT) systems.
-	•	Text Generation and Language Modeling.
+  - **Training NLP models**: Enables fine-tuning transformers for Myanmar language tasks.
+  - **Text-to-Speech (TTS)**: Provides diverse text for TTS synthesis models.
+  - **Automatic Speech Recognition (ASR)**: Aids in building language models for ASR systems.
+  - **Machine Translation (MT)**: Offers a resource for Myanmar-to-other-languages translation models.
+  - **Text Generation**: Supports training for Myanmar text generation models.
 
 ## License
 
-This dataset is licensed under the CC0 1.0 License. You are free to use, modify, and distribute the dataset without restrictions.
+This dataset is licensed under the [CC0 1.0 License](https://creativecommons.org/publicdomain/zero/1.0/). You are free to use, modify, and distribute the dataset without restrictions.
 
 ## Acknowledgments
 
 This dataset is derived from publicly available sources, including:
-	•	The Hugging Face FineWeb2 dataset, specifically its Myanmar subset.
-	•	Original writers, speakers, and creators of the sentences.
+  - The Hugging Face FineWeb2 dataset, specifically its Myanmar subset.
+  - Original writers, speakers, and creators of the sentences.
 
-The dataset has undergone significant manual and automated processing to create a distinct and valuable resource.
+The dataset has undergone extensive manual and automated processing to ensure quality and utility. These efforts included text cleaning, deduplication, and categorization.
 
 ## Citation