Update README.md

README.md

@@ -15,7 +15,74 @@ dataset_info:
     num_examples: 2000
   download_size: 797772747
   dataset_size: 717976082.0
+annotations_creators:
+- expert-generated
+language:
+- ml
+language_creators:
+- found
+license:
+- cc-by-sa-4.0
+multilinguality:
+- monolingual
+pretty_name: GEC Barton Hill Malayalam Speech Corpus
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+tags: []
+task_categories:
+- text-to-speech
+- automatic-speech-recognition
+task_ids: []
 ---
-# Dataset Card for "GMaSC"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# GMaSC: GEC Barton Hill Malayalam Speech Corpus
+
+**GMaSC** is a Malayalam text and speech corpus created by the Government Engineering College Barton Hill with an emphasis on Malayalam-accented English. The corpus contains 2,000 text-audio pairs of Malayalam sentences spoken by 2 speakers, totalling in approximately 139 minutes of audio. Each sentences has at least one English word common in Malayalam speech.
+
+## Dataset Structure
+The dataset consists of 2,000 instances with fields `text`, `speaker`, and `audio`. The audio is mono, sampled at 48kH. The transcription is normalized and only includes Malayalam characters and common punctuation. The table given below specifies how the 2,000 instances are split between the speakers, along with some basic speaker info:
+
+
+| Speaker | Gender | Age | Time (HH:MM:SS) | Sentences |
+| --- | --- | --- | --- | --- |
+| Sonia | Female | 43 | 01:02:17 | 1,000 |  
+| Anil | Male | 48 | 01:17:23 | 1,000 |  
+| **Total** | | | **02:19:40** | **2,000** |
+
+### Data Instances
+An example instance is given below:
+```json
+{'text': 'സൗജന്യ ആയുർവേദ മെഡിക്കൽ ക്യാമ്പ്',
+ 'speaker': 'Sonia',
+ 'audio': {'path': None,
+  'array': array([0.00036621, 0.00033569, 0.0005188 , ..., 0.00094604, 0.00091553,
+         0.00094604]),
+  'sampling_rate': 48000}}
+ ```
+
+### Data Fields
+- **text** (str): Transcription of the audio file
+- **speaker** (str): The name of the speaker
+- **audio** (dict): Audio object including loaded audio array, sampling rate and path to audio (always None)
+
+### Data Splits
+
+We provide all the data in a single `train` split. The loaded dataset object thus looks like this:
+```json
+DatasetDict({
+     train: Dataset({
+         features: ['text', 'speaker', 'audio'],
+         num_rows: 2000
+     })
+ })
+```
+
+## Additional Information
+
+### Licensing
+The corpus is made available under the [Creative Commons license (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/).
+
+
+