Update README.md

README.md

@@ -49,3 +49,53 @@ configs:
   - split: other
     path: data/other-*
 ---
+
+# Thai-TTS-Intelligibility-Eval
+
+**Thai-TTS-Intelligibility-Eval** is a curated evaluation set for measuring **intelligibility** of Thai Text-to-Speech (TTS) systems.  
+All 290 items are short, challenging phrases that commonly trip up phoneme-to-grapheme converters, prosody models, or pronunciation lexicons.  
+It is **not** intended for training; use it purely for benchmarking and regression tests.
+
+## Dataset Summary
+
+| Split   | #Utterances | Description                                                 |
+|---------|-------------|-------------------------------------------------------------|
+| `easy`  | 50          | Everyday phrases that most TTS systems should read correctly|
+| `medium`| 50          | More challening than easy                                   |
+| `hard`  | 50          | Hard phrases, e.g., mixed Thai and English and unique names |
+| `scbx`  | 50          | SCBX-specific terminology, products, and names              |
+| `name`  | 50          | Synthetic Thai personal names (mixed Thai & foreign roots)  |
+| `other` | 40          | Miscellaneous edge-cases not covered above                  |
+| **Total** | **290**   |                                                             |
+
+Each record contains:
+- **`id`** `string` Unique identifier  
+- **`text`** `string` sentence/phrase  
+- **`category`** `string` One of *easy, medium, hard, scbx, name, other*
+
+## Loading With 🤗 `datasets`
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset(
+    "scb10x/thai-tts-intelligiblity-eval",  # ← typo intentionally left? change if needed
+)
+ds_scbx = ds["scbx"]
+print(ds[0])
+# {'id': '53ef39464d9c1e6f', 'text': '...', 'category': 'scbx'}
+```
+
+## Intended Use
+
+1. **Objective evaluation**  
+   - *Compute WER/CER* between automatic transcripts of your TTS output and the gold reference text.
+   - Code: https://github.com/scb-10x/thai-tts-eval/tree/main/intelligibility
+2. **Subjective evaluation**  
+   - Conduct human listening tests (MOS, ABX, etc.)—the dataset is small enough for quick rounds.
+   - Future work
+4. **Regression testing**  
+   - Track intelligibility across model versions with a fixed set of hard sentences.
+   - Future work
+
+