updated dataset card

README.md

@@ -1,17 +1,17 @@
 ---
 pretty_name: 'Snow Mountain'
 language:
-- hi
-- bgc
-- kfs
-- dgo
-- bhd
-- gbk
-- xnr
-- kfx
-- mjl
-- kfo
-- bfz
+- hindi
+- haryanvi
+- dogri
+- gaddi
+- bilaspuri
+- bhadrawahi
+- kangri
+- kulvi
+- kulvi_outer_seraji
+- pahari_mahasui
+- mandeali
 annotations_creators:
 - ?
 language_creators:
@@ -74,7 +74,7 @@ dataset_info:
 
 ---
 
-# Dataset Card for [Dataset Name]
+# Dataset Card for [snow-mountain]
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -127,15 +127,27 @@ Hindi, Haryanvi, Bilaspuri, Dogri, Bhadrawahi, Gaddi, Kangri, Kulvi, Mandeali, K
 
 ### Data Instances
 
-[More Information Needed]
+A typical data point comprises the path to the audio file, usually called path and its transcription, called sentence. 
+
+```
+{'sentence': 'क्यूँके तू अपणी बात्तां कै कारण बेकसूर अर अपणी बात्तां ए कै कारण कसूरवार ठहराया जावैगा',
+ 'audio': {'path': 'data/cleaned/haryanvi/MAT/MAT_012_037.wav',
+  'array': array([0., 0., 0., ..., 0., 0., 0.]),
+  'sampling_rate': 16000},
+ 'path': 'data/cleaned/haryanvi/MAT/MAT_012_037.wav'}
+```
 
 ### Data Fields
 
-[More Information Needed]
+path: The path to the audio file
+
+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].
+
+sentence: the transcription of the audio file.
 
 ### Data Splits
 
-[More Information Needed]
+We create splits of the cleaned data for training and analysing the performance of ASR models. The splits are available in the `experiments` directory.  The file names indicate the experiment and the split category.
 
 ## Dataset Creation