Update README.md

README.md

@@ -46,9 +46,11 @@ configs:
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 # STOMA: A Multi-Speaker Greek Speech Corpus
-STOMA is a new multi-speaker Greek speech corpus designed to advance research in text-to-speech (TTS) synthesis and related speech technologies for under-resourced languages. The corpus comprises approximately 23 hours of professionally recorded read speech from six native speakers (three male and three female), captured under controlled studio conditions using a dual-booth setup to ensure acoustic consistency and high signal quality. The spoken material was selected from the Text Bank of the Center for the Greek Language, specifically from texts corresponding to the B2, C1, and C2 proficiency levels of the Certification of Attainment in Greek, ensuring linguistically rich and pedagogically balanced content. All recordings were standardized to 44.1 kHz, 16-bit mono PCM format and processed through a hybrid quality control pipeline combining automated normalization and manual verification. To assess dataset quality, we trained state-of-the-art neural TTS systems based on the FastSpeech2 acoustic model and the HiFi-GAN vocoder, achieving natural and intelligible synthesized speech. The resulting corpus provides a publicly accessible, high-quality resource that supports both linguistic research and the development of modern speech synthesis systems in Greek.
+**STOMA** is a new multi-speaker Greek speech corpus designed to advance research in text-to-speech (TTS) synthesis and related speech technologies for under-resourced languages. The corpus comprises approximately 23 hours of professionally recorded read speech from six native speakers (three male and three female), captured under controlled studio conditions using a dual-booth setup to ensure acoustic consistency and high signal quality. The spoken material was selected from the Text Bank of the Center for the Greek Language, specifically from texts corresponding to the B2, C1, and C2 proficiency levels of the Certification of Attainment in Greek, ensuring linguistically rich and pedagogically balanced content. All recordings were standardized to 44.1 kHz, 16-bit mono PCM format and processed through a hybrid quality control pipeline combining automated normalization and manual verification. To assess dataset quality, we trained state-of-the-art neural TTS systems based on the FastSpeech2 acoustic model and the HiFi-GAN vocoder, achieving natural and intelligible synthesized speech. The resulting corpus provides a publicly accessible, high-quality resource that supports both linguistic research and the development of modern speech synthesis systems in Greek.
 
 ## Dataset Structure
+**The dataset has been converted into a single file named "stoma_full.parquet". If you require the original folder structure, please contact us.**
+
 The dataset is organized into two main directories:
 * **Speakers/**: Contains the `.wav` audio files, organized by Speaker ID, Corpus Section, and Session.
 * **Text/**: Contains the `.txt` transcripts, organized by Corpus Section and Session.
@@ -73,8 +75,6 @@ Format: `Greek-<speaker>-<corpus>-<session>-<sentence>.wav`
 ## Usage
 You can load this dataset directly in Python using the Hugging Face `datasets` library. 
 
-**Note:** Ensure `stoma_metadata.csv` is present in the repository for the automatic mapping to work.
-
 ```python
 from datasets import load_dataset
 
@@ -93,7 +93,7 @@ sampling_rate = sample["audio"]["sampling_rate"]
 ```
 
 ## License
-STOMA is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
+**STOMA** is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
 
 
 ## More Information