Update README.md
Browse files
README.md
CHANGED
|
@@ -5,7 +5,7 @@ task_categories:
|
|
| 5 |
pretty_name: TunArTTS
|
| 6 |
---
|
| 7 |
|
| 8 |
-
Dataset:
|
| 9 |
|
| 10 |
This speech corpus is extracted from an online English-Tunisian Arabic dictionary Derja Ninja, providing a valuable resource for linguistic and speech-related research.
|
| 11 |
The dataset contains over 3 hours of mono-speaker audio recordings from a male speaker, sampled at 44.1 kHz.
|
|
@@ -22,4 +22,19 @@ Key characteristics of the corpus include:
|
|
| 22 |
|
| 23 |
This corpus is well-suited for applications such as speech synthesis and automatic speech recognition.
|
| 24 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 25 |
A research paper based on this dataset has been published. You can find the paper here: [https://aclanthology.org/2024.lrec-main.1467.pdf](#).
|
|
|
|
| 5 |
pretty_name: TunArTTS
|
| 6 |
---
|
| 7 |
|
| 8 |
+
# Dataset Description:
|
| 9 |
|
| 10 |
This speech corpus is extracted from an online English-Tunisian Arabic dictionary Derja Ninja, providing a valuable resource for linguistic and speech-related research.
|
| 11 |
The dataset contains over 3 hours of mono-speaker audio recordings from a male speaker, sampled at 44.1 kHz.
|
|
|
|
| 22 |
|
| 23 |
This corpus is well-suited for applications such as speech synthesis and automatic speech recognition.
|
| 24 |
|
| 25 |
+
# Dataset Characteristics
|
| 26 |
+
|
| 27 |
+
| **Characteristic** | **Value** |
|
| 28 |
+
|-----------------------------|--------------------------------|
|
| 29 |
+
| Total Segments | 1493 |
|
| 30 |
+
| Total Words | 20925 |
|
| 31 |
+
| Total Characters | 113221 |
|
| 32 |
+
| Total Duration | 3 hours and 32 seconds |
|
| 33 |
+
| Mean Clip Duration | 7.24 seconds |
|
| 34 |
+
| Min Clip Duration | 3.11 seconds |
|
| 35 |
+
| Max Clip Duration | 16.3 seconds |
|
| 36 |
+
| Mean Words per Clip | 14.015 |
|
| 37 |
+
| Distinct Words | 4491 |
|
| 38 |
+
|
| 39 |
+
|
| 40 |
A research paper based on this dataset has been published. You can find the paper here: [https://aclanthology.org/2024.lrec-main.1467.pdf](#).
|