Update README.md

README.md

@@ -21,4 +21,61 @@ dataset_info:
     num_examples: 205
   download_size: 3201049372
   dataset_size: 13172835766
+task_categories:
+- text-to-speech
+- text-to-audio
+- auto-diacritization
+language:
+- ar
+pretty_name: ClArTTS
+size_categories:
+- 1K<n<10K
+multiliguality: monolingual
 ---
+
+# Dataset Card for ClArTTS
+
+## Dataset Description
+- **Homepage:** [ClArTTS](http://www.clartts.com/)
+- **Paper:** [ClARTTS: An Open-Source Classical Arabic Text-to-Speech Corpus](https://www.isca-archive.org/interspeech_2023/kulkarni23_interspeech.pdf)
+
+### Dataset Summary
+We present a speech corpus for Classical Arabic Text-to-Speech (ClArTTS) to support the development of end-to-end TTS systems for Arabic. The speech is extracted from a LibriVox audiobook, whichis then processed, segmented, and manually transcribed and annotated. The final ClArTTS corpus contains about 12 hours of speech from a single male speaker sampled at 40100 kHz.
+
+## Dataset Structure
+### Data Instances
+
+A typical data point comprises the name of the audio file, called 'file', its transcription, called `text`, the audio as an array, called 'audio'. Some additional information; sampling rate and audio duration.
+
+```
+DatasetDict({
+    train: Dataset({
+        features: ['text', 'file', 'audio', 'sampling_rate', 'duration'],
+        num_rows: 9500
+    })
+    test: Dataset({
+        features: ['text', 'file', 'audio', 'sampling_rate', 'duration'],
+        num_rows: 205
+    })
+})
+```
+
+### Data Splits
+Data is divided into two sets;
+
+train: with 9500 audio samples.
+test: with 205 audio samples.
+
+
+### Citation Information
+```
+@inproceedings{kulkarni2023clartts,
+  author={Ajinkya Kulkarni and Atharva Kulkarni and Sara Abedalmon'em Mohammad Shatnawi and Hanan Aldarmaki},
+  title={ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus},
+  year={2023},
+  booktitle={2023 INTERSPEECH },
+  pages={5511--5515},
+  doi={10.21437/Interspeech.2023-2224}
+}
+
+```