Datasets:
Languages:
Greek
Size:
10K - 100K
Tags:
speech_corpus
greek_language
text-to-speech
neural_TTS
speech_synthesis
under_resourced_languages
License:
File size: 14,618 Bytes
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pretty_name: 'STOMA: A Multi-Speaker Greek Speech Corpus'
annotations_creators:
- expert-generated
language:
- el
license: cc-by-4.0
task_categories:
- text-to-speech
- automatic-speech-recognition
- audio-classification
tags:
- speech_corpus
- greek_language
- text-to-speech
- neural_TTS
- speech_synthesis
- under_resourced_languages
- audio
size_categories:
- 10K<n<100K
---
# 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 Greek, an under-resourced language. The corpus comprises approximately 23 hours of studio-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 Greek Harvard Corpus and 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 well-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 is provided in sharded Parquet format for optimized loading. The original folder structure ("Speakers/" and "Text/") and naming conventions are preserved as metadata features ("speaker_id", "section", "session", etc.) within the dataset.**
## Data Fields
When you load the dataset, the metadata originally encoded in the raw file names is automatically parsed into the following distinct columns for easier filtering and analysis:
* **`speaker_id`** *(string)*: The speaker identifier.
* `M`: Main Male Speaker
* `F`: Main Female Speaker
* `M1`...`MX`: Other Male Speakers
* `F1`...`FX`: Other Female Speakers
* **`section`** *(string)*: The section of the corpus the text originated from (e.g., `Harvard`, `B2`, `C1`, `C2`).
* **`session`** *(int64)*: The recording session number.
* **`sentence_id`** *(int64)*: The unique sentence identifier within that specific session.
* **`text`** *(string)*: The Greek transcript of the audio.
* **`audio`** *(audio)*: The loaded audio feature, which includes the raw audio array and the sampling rate.
* **`file_name`** *(string)*: The original filename of the source `.wav` audio file (e.g., `Greek-F1-B2-05-20.wav`).
## Usage
You can load this dataset directly in Python using the Hugging Face `datasets` library.
```python
from datasets import load_dataset
# Download and Load the dataset
dataset = load_dataset("aangelakis/STOMA", split="train")
# Inspect the first example
sample = dataset[0]
# Print the Greek text
print("Text:", sample["text"])
# Print metadata
print("Speaker:", sample["speaker_id"])
print("Corpus Section:", sample["section"])
print("Session:", sample["session"])
print("Sentence ID:", sample["sentence_id"])
print("Original File Name:", sample["file_name"])
# The 'audio' column is automatically decoded into a dictionary with 'array' and 'sampling_rate'
audio_data = sample["audio"]["array"]
sampling_rate = sample["audio"]["sampling_rate"]
```
## License
**STOMA** is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
## Citation
If you use this work, please cite:
```bibtex
TBA
```
## References
- **Michail Raptakis** - mrap@csd.uoc.gr (University of Crete, IACM-FORTH)
- **Yannis Pantazis** - pantazis@iacm.forth.gr (IACM-FORTH)
- **Alexandros Angelakis** - angelakis@csd.uoc.gr (University of Crete, IACM-FORTH)
## More Information
Check out our GitHub repository for the training and inference procedures: [STOMA: A Multi-Speaker Greek Speech Corpus](https://github.com/aangelakis/STOMA)
<div align="center">
<strong>Table 1: Text statistics for the full text collection (Greek Harvard, B2, C1, and C2), recorded in its entirety by the two primary speakers.</strong>
<table>
<thead>
<tr>
<th>Statistic</th>
<th>Gr. Harvard</th>
<th>B2</th>
<th>C1</th>
<th>C2</th>
<th>Total</th>
</tr>
</thead>
<tbody>
<tr>
<td>Total Sentences</td>
<td align="center">720</td>
<td align="center">1,087</td>
<td align="center">1,571</td>
<td align="center">1,296</td>
<td align="center">4,674</td>
</tr>
<tr>
<td>Total Words</td>
<td align="center">5,539</td>
<td align="center">15,102</td>
<td align="center">25,263</td>
<td align="center">22,722</td>
<td align="center">68,626</td>
</tr>
<tr>
<td>Total Characters</td>
<td align="center">32,301</td>
<td align="center">95,119</td>
<td align="center">164,700</td>
<td align="center">152,904</td>
<td align="center">445,024</td>
</tr>
<tr>
<td>Distinct Words</td>
<td align="center">3,343</td>
<td align="center">5,606</td>
<td align="center">8,965</td>
<td align="center">8,275</td>
<td align="center">20,253</td>
</tr>
<tr>
<td>Mean Words per Sentence</td>
<td align="center">7.69</td>
<td align="center">13.89</td>
<td align="center">16.08</td>
<td align="center">17.53</td>
<td align="center">14.68</td>
</tr>
<tr>
<td>Min Words per Sentence</td>
<td align="center">5</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
</tr>
<tr>
<td>Max Words per Sentence</td>
<td align="center">9</td>
<td align="center">32</td>
<td align="center">41</td>
<td align="center">39</td>
<td align="center">41</td>
</tr>
</tbody>
</table>
</div>
<div align="center">
<strong>Table 2: Text statistics for the reduced text subset selected from the full collection, used for recordings by the secondary speakers.</strong>
<table>
<thead>
<tr>
<th>Statistic</th>
<th>Gr. Harvard</th>
<th>B2</th>
<th>C1</th>
<th>C2</th>
<th>Subset Total</th>
</tr>
</thead>
<tbody>
<tr>
<td>Total Sentences</td>
<td align="center">720</td>
<td align="center">190</td>
<td align="center">194</td>
<td align="center">197</td>
<td align="center">1,301</td>
</tr>
<tr>
<td>Total Words</td>
<td align="center">5,539</td>
<td align="center">2,913</td>
<td align="center">3,057</td>
<td align="center">3,265</td>
<td align="center">14,774</td>
</tr>
<tr>
<td>Total Characters</td>
<td align="center">32,301</td>
<td align="center">18,286</td>
<td align="center">20,190</td>
<td align="center">22,110</td>
<td align="center">92,887</td>
</tr>
<tr>
<td>Distinct Words</td>
<td align="center">3,343</td>
<td align="center">1,519</td>
<td align="center">1,604</td>
<td align="center">1,676</td>
<td align="center">6,899</td>
</tr>
<tr>
<td>Mean Words per Sentence</td>
<td align="center">7.69</td>
<td align="center">15.33</td>
<td align="center">15.76</td>
<td align="center">16.57</td>
<td align="center">11.36</td>
</tr>
<tr>
<td>Min Words per Sentence</td>
<td align="center">5</td>
<td align="center">4</td>
<td align="center">3</td>
<td align="center">4</td>
<td align="center">3</td>
</tr>
<tr>
<td>Max Words per Sentence</td>
<td align="center">9</td>
<td align="center">28</td>
<td align="center">28</td>
<td align="center">30</td>
<td align="center">30</td>
</tr>
</tbody>
</table>
</div>
<div align="center">
<strong>Table 3: Speech statistics of the STOMA corpus per speaker and overall.</strong>
<table>
<thead>
<tr>
<th>Speaker ID</th>
<th>Clips</th>
<th>Total Duration</th>
<th>Mean Duration (s)</th>
<th>Min–Max (s)</th>
</tr>
</thead>
<tbody>
<tr>
<td>F</td>
<td align="center">4,674</td>
<td align="center">7:46:21</td>
<td align="center">5.99</td>
<td align="center">0.41–16.60</td>
</tr>
<tr>
<td>M</td>
<td align="center">4,674</td>
<td align="center">8:53:37</td>
<td align="center">6.85</td>
<td align="center">0.48–22.31</td>
</tr>
<tr>
<td>F1</td>
<td align="center">1,301</td>
<td align="center">1:46:58</td>
<td align="center">4.93</td>
<td align="center">1.65–15.08</td>
</tr>
<tr>
<td>F2</td>
<td align="center">1,301</td>
<td align="center">1:27:38</td>
<td align="center">4.04</td>
<td align="center">1.46–11.13</td>
</tr>
<tr>
<td>M1</td>
<td align="center">1,301</td>
<td align="center">1:47:06</td>
<td align="center">4.94</td>
<td align="center">1.64–14.99</td>
</tr>
<tr>
<td>M2</td>
<td align="center">1,301</td>
<td align="center">1:26:43</td>
<td align="center">4.00</td>
<td align="center">1.10–10.39</td>
</tr>
<tr>
<td><strong>Total</strong></td>
<td align="center"><strong>14,552</strong></td>
<td align="center"><strong>23:08:26</strong></td>
<td align="center"><strong>5.72</strong></td>
<td align="center"><strong>0.41–22.31</strong></td>
</tr>
</tbody>
</table>
</div>
<div align="center">
<strong>Table 4: Speaker-specific acoustic characteristics of the STOMA corpus. SR: average speech rate (syllables/s, including pauses); AR: average articulation rate (syllables/s, excluding pauses); ASD: average syllable duration (s), computed across all utterances per speaker.</strong>
<table>
<thead>
<tr>
<th>Speaker ID</th>
<th>Mean F0 (Hz)</th>
<th>Std F0 (Hz)</th>
<th>SR</th>
<th>AR</th>
<th>ASD (s)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="center">M</td>
<td align="center">118.73</td>
<td align="center">20.80</td>
<td align="center">4.143</td>
<td align="center">4.286</td>
<td align="center">0.236</td>
</tr>
<tr>
<td align="center">F</td>
<td align="center">195.53</td>
<td align="center">40.16</td>
<td align="center">4.462</td>
<td align="center">4.662</td>
<td align="center">0.218</td>
</tr>
<tr>
<td align="center">M1</td>
<td align="center">128.30</td>
<td align="center">23.34</td>
<td align="center">4.165</td>
<td align="center">4.403</td>
<td align="center">0.230</td>
</tr>
<tr>
<td align="center">F1</td>
<td align="center">200.93</td>
<td align="center">23.57</td>
<td align="center">3.887</td>
<td align="center">3.974</td>
<td align="center">0.257</td>
</tr>
<tr>
<td align="center">M2</td>
<td align="center">109.33</td>
<td align="center">15.49</td>
<td align="center">4.407</td>
<td align="center">4.527</td>
<td align="center">0.225</td>
</tr>
<tr>
<td align="center">F2</td>
<td align="center">187.29</td>
<td align="center">26.88</td>
<td align="center">4.238</td>
<td align="center">4.409</td>
<td align="center">0.232</td>
</tr>
</tbody>
</table>
</div>
<div align="center">
<strong>Table 5: Demographic information of the STOMA corpus speakers.</strong>
<table>
<thead>
<tr>
<th>Speaker ID</th>
<th>Age</th>
<th>Sex</th>
<th>Region Raised</th>
</tr>
</thead>
<tbody>
<tr>
<td align="center">M</td>
<td align="center">29</td>
<td align="center">Male</td>
<td align="center">Athens</td>
</tr>
<tr>
<td align="center">F</td>
<td align="center">37</td>
<td align="center">Female</td>
<td align="center">Crete</td>
</tr>
<tr>
<td align="center">M1</td>
<td align="center">30</td>
<td align="center">Male</td>
<td align="center">Alexandroupoli</td>
</tr>
<tr>
<td align="center">F1</td>
<td align="center">21</td>
<td align="center">Female</td>
<td align="center">Larisa</td>
</tr>
<tr>
<td align="center">M2</td>
<td align="center">22</td>
<td align="center">Male</td>
<td align="center">Larisa</td>
</tr>
<tr>
<td align="center">F2</td>
<td align="center">26</td>
<td align="center">Female</td>
<td align="center">Athens</td>
</tr>
</tbody>
</table>
</div>
<div align="center">
<strong>Table 6: Audio format specifications of the STOMA corpus recordings.</strong>
<table>
<thead>
<tr>
<th>Property</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>File format</td>
<td>WAV (RIFF)</td>
</tr>
<tr>
<td>Encoding</td>
<td>Pulse-Code Modulation (PCM)</td>
</tr>
<tr>
<td>Compression</td>
<td>None (uncompressed)</td>
</tr>
<tr>
<td>Channels</td>
<td>1 (mono)</td>
</tr>
<tr>
<td>Sampling rate</td>
<td>44.1 kHz</td>
</tr>
<tr>
<td>Bit depth</td>
<td>16-bit signed integer</td>
</tr>
</tbody>
</table>
</div>
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