Update README.md

README.md

@@ -35,10 +35,10 @@ tags:
 This model is designed to support **phoneme-based text-to-speech (TTS) systems**, including but not limited to [StyleTTS2](https://github.com/yl4579/StyleTTS2). Thanks to its Spanish-specific phoneme vocabulary and contextual embedding capabilities, it can serve as a phoneme encoder for any TTS architecture requiring phoneme-level features.
 
 Features of our PL-BERT:
-- It is trained **exclusively on Spanish** phonemized text.
-- It uses a reduced **phoneme vocabulary of 178 tokens**.
-- It uses wordpiece tokenizer.
-- It includes a custom `token_maps.pkl` and adapted `util.py`.
+- It is trained **exclusively on Spanish** phonemized text
+- It uses a reduced **phoneme vocabulary of 178 tokens**
+- It uses wordpiece tokenizer
+- It includes a custom `token_maps.pkl` and adapted `util.py`
 
 ---
 
@@ -46,15 +46,15 @@ Features of our PL-BERT:
 
 ### Intended uses
 
-- Integration into phoneme-based TTS pipelines such as StyleTTS2, Matxa-TTS, or custom diffusion-based synthesizers.
-- Accent-aware synthesis and phoneme embedding extraction for Spanish.
+- Integration into phoneme-based TTS pipelines such as StyleTTS2, Matxa-TTS, or custom diffusion-based synthesizers
+- Accent-aware synthesis and phoneme embedding extraction for Spanish
 
 
 ### Limitations
 
-- Not designed for general NLP tasks like classification or sentiment analysis.
-- Only supports Spanish phoneme tokens.
-- Some accents may be underrepresented in the training data.
+- Not designed for general NLP tasks like classification or sentiment analysis
+- Only supports Spanish phoneme tokens
+- Some accents may be underrepresented in the training data
 
 ---
 
@@ -78,7 +78,7 @@ Here is an example of how to use this model within the StyleTTS2 framework:
 
    `from Utils.PLBERT_es.util import load_plbert`
 
-6. Use `espeak-ng` with the language code `es-419` to phonemize your Spanish text files for training and validation.
+6. Phonemize your Spanish text files for training and validation (if you consider `espeak-ng` use the language code `es-419`)
 
 Note: Although this example uses StyleTTS2, the model is compatible with other TTS architectures that operate on phoneme sequences. You can use the contextualized phoneme embeddings from PL-BERT in any compatible synthesis system.
 
@@ -88,7 +88,7 @@ Note: Although this example uses StyleTTS2, the model is compatible with other T
 
 ### Training data
 
-The model was trained on a Spanish corpus phonemized using espeak-ng. It uses a consistent phoneme token set with boundary markers and masking tokens.
+The model was trained on a phonemized Spanish corpus (any phonemizer can be used). It uses a consistent phoneme token set with boundary markers and masking tokens.
 
 Tokenizer: custom (split using whitespaces)  
 Phoneme masking strategy: word-level and phoneme-level masking and replacement  
@@ -134,7 +134,7 @@ If this code contributes to your research, please cite the work:
       title={PL-BERT-wp-es}, 
       author={Rodolfo Zevallos, Jose Giraldo and Carme Armentano-Oller},
       organization={Barcelona Supercomputing Center},
-      url={https://huggingface.co/langtech-veu/PL-BERT-wp_es},
+      url={https://huggingface.co/BSC-LT/PL-BERT-wp-es},
       year={2025}
 }
 ```