Update README.md

Accentuate which dataset was used in the paper

README.md

@@ -18,7 +18,7 @@ size_categories:
 
 # ARCTIC-HS
 
-An extension of the [CMU_ARCTIC](http://festvox.org/cmu_arctic/) and [L2-ARCTIC](https://psi.engr.tamu.edu/l2-arctic-corpus/) datasets for synthetic speech detection using text-to-speech, featured in the paper **Synthetic speech detection with Wav2Vec 2.0 in various language settings**.
+An extension of the [CMU_ARCTIC](http://festvox.org/cmu_arctic/) and [L2-ARCTIC](https://psi.engr.tamu.edu/l2-arctic-corpus/) datasets for synthetic speech detection using text-to-speech, featured in the paper **Synthetic speech detection with Wav2Vec 2.0 in various language settings**. Specifically, the `symmetric` variants were used.
 
 This dataset is 1 of 3 used in the paper, the others being:
 - [FLEURS-HS](https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs)
@@ -93,7 +93,7 @@ To load a different part, change `cmu_non-us` into one of the following:
 
 This dataset only has a `test` split.
 
-To load only the paired samples, append `_symmetric` to the name. For example, `cmu_non-us` will load the test set also containing human and synthetic samples without their counterpart, while `cmu_non-us_symmetric` will only load samples where there is both a human and synthetic variant. This is useful if you want to have perfectly balanced labels within speakers, and if you wish to exclude speakers for which there are no TTS counterparts at all.
+To load only the paired samples, append `_symmetric` to the name. For example, `cmu_non-us` will load the test set also containing human and synthetic samples without their counterpart, while `cmu_non-us_symmetric` will only load samples where there is both a human and synthetic variant. This is useful if you want to have perfectly balanced labels within speakers, and if you wish to exclude speakers for which there are no TTS counterparts at all. This is also the family of datasets used in the paper.
 
 The `trust_remote_code=True` parameter is necessary because this dataset uses a custom loader. To check out which code is being ran, check out the [loading script](./arctic-hs.py).