commit

README.md

@@ -90,6 +90,26 @@ This dataset is intended for:
 - Benchmarking STT systems on varied speaking styles
 - Development and testing of speech recognition pipelines
 
+## Recommended Evaluation Packages
+
+For WER (Word Error Rate) evaluation, we recommend using text normalization to handle variations in number formatting, punctuation, and casing:
+
+- **[whisper-normalizer](https://pypi.org/project/whisper-normalizer/)**: Text normalization for STT evaluation (handles "3000" vs "three thousand", punctuation, casing)
+- **[werpy](https://pypi.org/project/werpy/)**: WER calculation with detailed error analysis
+
+```python
+from whisper_normalizer.english import EnglishTextNormalizer
+from werpy import wer
+
+normalizer = EnglishTextNormalizer()
+
+# Normalize both reference and hypothesis before comparison
+reference = normalizer(ground_truth)
+hypothesis = normalizer(model_output)
+
+error_rate = wer(reference, hypothesis)
+```
+
 ## Limitations
 
 - Small dataset size (92 samples)