Remove 0.1 version

README.md

@@ -498,9 +498,9 @@ configs:
   - split: train
     path: data/Youtube_TV_VCA/train/train-*
 ---
-# LinTO DataSet Audio for Arabic Tunisian Augmented v0.1 <br />*A collection of Tunisian dialect audio and its annotations for STT task*
+# LinTO DataSet Audio for Arabic Tunisian Augmented <br />*A collection of Tunisian dialect audio and its annotations for STT task*
 
-This is the augmented datasets used to train the Linto Tunisian dialect with code-switching STT [linagora/linto-asr-ar-tn-0.1](https://huggingface.co/linagora/linto-asr-ar-tn-0.1).
+This is the augmented datasets used to train the Linto Tunisian dialect with code-switching STT [linagora/linto-asr-ar-tn](https://huggingface.co/linagora/linto-asr-ar-tn).
 
 * [Dataset Summary](#dataset-summary)
 * [Dataset composition](#dataset-composition)
@@ -513,11 +513,11 @@ This is the augmented datasets used to train the Linto Tunisian dialect with cod
 
 ## Dataset Summary
 
-The **LinTO DataSet Audio for Arabic Tunisian Augmented v0.1** is a dataset that builds on [**LinTO DataSet Audio for Arabic Tunisian v0.1**](https://huggingface.co/datasets/linagora/linto-dataset-audio-ar-tn-0.1), using a subset of the original audio data. Augmentation techniques, including noise reduction and SoftVC VITS Singing Voice Conversion (SVC), have been applied to enhance the dataset for improved performance in Arabic Tunisian Automatic Speech Recognition (ASR) tasks.
+The **LinTO DataSet Audio for Arabic Tunisian Augmented** is a dataset that builds on [**LinTO DataSet Audio for Arabic Tunisian**](https://huggingface.co/datasets/linagora/linto-dataset-audio-ar-tn), using a subset of the original audio data. Augmentation techniques, including noise reduction and SoftVC VITS Singing Voice Conversion (SVC), have been applied to enhance the dataset for improved performance in Arabic Tunisian Automatic Speech Recognition (ASR) tasks.
 
 ## Dataset Composition:
 
-The **LinTO DataSet Audio for Arabic Tunisian Augmented v0.1** comprises a diverse range of augmented audio samples using different techniques. Below is a breakdown of the dataset’s composition:
+The **LinTO DataSet Audio for Arabic Tunisian Augmented** comprises a diverse range of augmented audio samples using different techniques. Below is a breakdown of the dataset’s composition:
 
 ### Sources
 
@@ -548,7 +548,7 @@ The **LinTO DataSet Audio for Arabic Tunisian Augmented v0.1** comprises a diver
 
 The image below shows the difference between the original and the augmented audio:
 
-![Wave Interface](https://huggingface.co/datasets/linagora/linto-dataset-audio-ar-tn-augmented-0.1/resolve/main/img.png)
+![Wave Interface](img.png)
 
 - The first row shows the original waveform.
 - The second row shows the audio after noise reduction.
@@ -581,7 +581,7 @@ The image below shows the difference between the original and the augmented audi
 from datasets import load_dataset
 
 # dataset will be loaded as a DatasetDict of train and test
-dataset = load_dataset("linagora/linto-dataset-audio-ar-tn-augmented-0.1")
+dataset = load_dataset("linagora/linto-dataset-audio-ar-tn-augmented")
 ```
 
 Check the containt of dataset:
@@ -606,16 +606,16 @@ segments: [{'end': 14.113, 'start': 0.0, 'transcript': 'أسبقية قبل أن
 Given that some of the corpora used for training and evaluation are available only under CC-BY-4.0 licenses, we have chosen to license the entire dataset under CC-BY-4.0.
 
 ## Citations
-When using the **LinTO DataSet Audio for Arabic Tunisian v0.1** corpus, please cite this page:
+When using the **LinTO DataSet Audio for Arabic Tunisian** corpus, please cite this page:
 
 ```bibtex
 @misc{linagora2024Linto-tn,
   author = {Hedi Naouara and Jérôme Louradour and Jean-Pierre Lorré and Sarah zribi and Wajdi Ghezaiel},
-  title = {LinTO DataSet Audio for Arabic Tunisian v0.1},
+  title = {LinTO DataSet Audio for Arabic Tunisian},
   year = {2024},
   publisher = {HuggingFace},
   journal = {HuggingFace},
-  howpublished = {\url{https://huggingface.co/datasets/linagora/linto-dataset-audio-ar-tn-0.1}},
+  howpublished = {\url{https://huggingface.co/datasets/linagora/linto-dataset-audio-ar-tn}},
 }
 ```