Update README.md

README.md

@@ -15,6 +15,7 @@ tags:
 - Aholab
 - Ilenia
 - synthetic
+- common-voice
 base_model:
 - itzune/maider-tts
 ---
@@ -23,19 +24,17 @@ base_model:
 
 This is a large-scale **synthetic speech corpus** designed for training and fine-tuning Basque Text-to-Speech (TTS) models. It consists of **99,996 audio files** synthesized from the "Maider" voice model.
 
-This dataset was generated by **Itzune** and serves as the primary source for training the [itzune/maider-tts (Piper version)](https://huggingface.co/itzune/maider-tts) model, enabling high-quality Basque synthesis in edge-compatible formats.
+This dataset was generated by **Itzune** and serves as the primary source for training the [itzune/maider-tts (Piper version)](https://huggingface.co/itzune/maider-tts) model.
 
 ## Dataset Structure
 
 Due to the large volume of data (approx. 100,000 files), the dataset is organized in the **WebDataset** format. The audio files are bundled into `.tar` shards to optimize storage, I/O performance, and streaming.
 
-
-
 ### Files
-- **data/**: Directory containing the `.tar` shards. Each shard contains approximately 1,000 audio samples.
-- **metadata.csv**: The main metadata file using `|` as a delimiter. It follows this structure:
+- **data/**: Directory containing the `.tar` shards.
+- **metadata.csv**: The main metadata file using `|` as a delimiter:
   - `file_name`: The name of the audio file (e.g., `audio_1.wav`).
-  - `transcription`: The corresponding Basque text used for synthesis.
+  - `transcription`: The corresponding Basque text.
 
 ## Technical Specifications
 
@@ -43,38 +42,41 @@ Due to the large volume of data (approx. 100,000 files), the dataset is organize
 - **Sample Rate:** 22050 Hz
 - **Language:** Basque (eu)
 - **Voice Profile:** Maider (Female)
-- **Total Samples:** 99,996
+- **Text Source:** [Mozilla Common Voice - Basque Sentence Collection](https://datacollective.mozillafoundation.org/datasets/cmj8u3p2v007tnxxbk5ng5qvh)
 - **Generation Method:** Synthesized using VITS-based architecture.
 
 ## Usage
 
-You can load this dataset using the Hugging Face `datasets` library. Using `streaming=True` is highly recommended to avoid downloading the entire 100k files at once:
-
 ```python
 from datasets import load_dataset
 
 dataset = load_dataset("itzune/maider-dataset", streaming=True)
-
-# View an example
 sample = next(iter(dataset["train"]))
 print(f"Text: {sample['transcription']}")
 ```
 
 ## Credits and Licensing
-
 ### Source and Methodology
-This is a **synthetic dataset** generated by **Itzune**. It was created using the `aHoTTS` synthesis tools provided by **HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory**. 
 
-The audio files were synthesized using the pre-trained **Maider (VITS)** model, following the methodology described in the HiTZ/Aholab repository. This dataset serves as a large-scale synthetic corpus for downstream tasks, such as exporting models to edge-compatible formats (e.g., Piper).
+This is a synthetic dataset generated by Itzune. The synthesis process involved:
+
+- **Text Acquisition**: Sentences were sourced from the Mozilla Common Voice project (Basque sentence collection).
+
+- **Audio Synthesis**: The audio was produced using the aHoTTS synthesis tools and the pre-trained Maider (VITS) model developed by HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory.
 
 ### Acknowledgments
-The underlying technology and the original voice models were developed by:
-- **HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory**, University of the Basque Country (UPV/EHU).
-- **Project ILENIA:** The Maider voice resource was developed with funding from Project ILENIA.
+
+    Mozilla Common Voice: For providing the community-driven sentence collection.
+
+    HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory: For the underlying synthesis technology and the Maider voice model.
+
+    Project ILENIA: The original Maider voice resource was developed with funding from Project ILENIA.
 
 ### License
-- **Dataset Content:** Licensed under [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).
-- **Original Tools/Code:** The tools used to generate this data are licensed under the **Apache License 2.0** by the original authors.
+
+    Dataset Content (Audio & Text): Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).
+
+    Original Tools/Code: The aHoTTS tools used to generate this data are licensed under the Apache License 2.0.
 
 ## Citation
 If you use this dataset, please cite the original work from HiTZ/Aholab: