Update README.md

README.md

@@ -88,11 +88,11 @@ train-eval-index:
 
 - **Homepage:** [Tarteel AI](https://www.tarteel.ai/)
 - **Repository:** [Needs More Information]
-- **Point of Contact:** [Nawar Halabi](mailto:ms.ibnseddik@tarteel.ai)
+- **Point of Contact:** [Mohamed Saad Ibn Seddik](mailto:ms.ibnseddik@tarteel.ai)
 
 ### Dataset Summary
 
-This Speech corpus has been developed as part of PhD work carried out by Nawar Halabi at the University of Southampton. The corpus was recorded in south Levantine Arabic (Damascian accent) using a professional studio. Synthesized speech as an output using this corpus has produced a high quality, natural voice.
+This dataset is a collection of Quranic verses and their transcriptions, with diacritization, by different reciters.
 
 ### Supported Tasks and Leaderboards
 
@@ -106,31 +106,33 @@ The audio is in Arabic.
 
 ### Data Instances
 
-A typical data point comprises the path to the audio file, usually called `file` and its transcription, called `text`.
+A typical data point comprises the audio file `audio`, and its transcription called `text`.
+The `duration` is in seconds, and the author is `reciter`.
+
 An example from the dataset is:
 ```
 {
-    'file': '/Users/username/.cache/huggingface/datasets/downloads/extracted/baebe85e2cb67579f6f88e7117a87888c1ace390f4f14cb6c3e585c517ad9db0/arabic-speech-corpus/wav/ARA NORM  0002.wav',
-	'audio': {'path': '/Users/username/.cache/huggingface/datasets/downloads/extracted/baebe85e2cb67579f6f88e7117a87888c1ace390f4f14cb6c3e585c517ad9db0/arabic-speech-corpus/wav/ARA NORM  0002.wav',
-			   'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32),
-			   'sampling_rate': 48000},
-		'orthographic': 'waraj~aHa Alt~aqoriyru Al~a*iy >aEad~ahu maEohadu >aboHaA^i haDabapi Alt~ibiti fiy Alo>akaAdiymiy~api AlS~iyniy~api liloEuluwmi - >ano tasotamir~a darajaAtu AloHaraArapi wamusotawayaAtu Alr~uTuwbapi fiy Alo<irotifaAEi TawaAla ha*aA Aloqarono',
-    'phonetic': "sil w a r a' jj A H a tt A q r ii0' r u0 ll a * i0 < a E a' dd a h u0 m a' E h a d u0 < a b H aa' ^ i0 h A D A' b a t i0 tt i1' b t i0 f i0 l < a k aa d ii0 m ii0' y a t i0 SS II0 n ii0' y a t i0 l u0 l E u0 l uu0' m i0 sil < a' n t a s t a m i0' rr a d a r a j aa' t u0 l H a r aa' r a t i0 w a m u0 s t a w a y aa' t u0 rr U0 T UU0' b a t i0 f i0 l Ah i0 r t i0 f aa' E i0 T A' w A l a h aa' * a l q A' r n sil",
-    'text': '\ufeffwaraj~aHa Alt~aqoriyru Al~aTHiy >aEad~ahu maEohadu >aboHaA^i haDabapi Alt~ibiti fiy Alo>akaAdiymiy~api AlS~iyniy~api liloEuluwmi - >ano tasotamir~a darajaAtu AloHaraArapi wamusotawayaAtu Alr~uTuwbapi fiy Alo<irotifaAEi TawaAla haTHaA Aloqarono'
+  'audio': {
+    'path': None,
+    'array': array([ 0.        ,  0.        ,  0.        , ..., -0.00057983,
+       -0.00085449, -0.00061035]),
+    'sampling_rate': 16000
+  },
+  'duration': 6.478375,
+  'text': 'بِسْمِ اللَّهِ الرَّحْمَنِ الرَّحِيمِ',
+  'reciter': 'abdulsamad'
 }
 ```
 
 ### Data Fields
 
-- file: A path to the downloaded audio file in .wav format.
-
 - audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
 
-- text: the transcription of the audio file.
+- text: The transcription of the audio file.
 
-- phonetic: the transcription in phonentics format. 
+- duration: The duration of the audio file. 
 
-- orthographic: the transcriptions written in orthographic format. 
+- reciter: The reciter of the verses. 
 
 ### Data Splits