Update README.md to reflect code changes

README.md

@@ -49,13 +49,13 @@ The dataset features 8 languages originally seen in FLEURS:
 - Polish
 - Swedish
 
-The original FLEURS samples are used as `human` samples, while `synthetic` samples are generated using:
+The `synthetic` samples are generated using:
 
 - [Google Cloud Text-To-Speech](https://cloud.google.com/text-to-speech)
 - [Azure Text-To-Speech](https://azure.microsoft.com/en-us/products/ai-services/text-to-speech)
 - [Amazon Polly](https://aws.amazon.com/polly/)
 
-The resulting dataset features roughly twice the samples per language (every `human` sample usually has its `synthetic` counterpart).
+Only the test VITS samples are provided. For every VITS voice, which is in practice specific model weights, one sample per transcript is provided.
 
 
 - **Curated by:** [KONTXT by RealNetworks](https://realnetworks.com/kontxt)
@@ -74,7 +74,7 @@ The original FLEURS dataset was downloaded from [HuggingFace](https://huggingfac
 
 ## Uses
 
-This dataset is best used as a difficult test set. Each sample contains an `Audio` feature, and a label: `human` or `synthetic`.
+This dataset is best used as a difficult test set. Each sample contains an `Audio` feature, and a label, which is always `synthetic`; this dataset does not include any human samples.
 
 ### Direct Use
 
@@ -102,8 +102,6 @@ To load a different language, change `en_us` into one of the following:
 
 This dataset only has a `test` split.
 
-To load only the synthetic samples, append `_without-human` to the name. For example, `en_us` will load the test set also containing the original English FLEURS samples, while `en_us_without-human` will only load the synthetic VITS samples. This is useful if you simply want to include the VITS samples into the original FLEURS-HS test set without duplicating human samples.
-
 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](./fleurs-hs-vits.py).
 
 ## Dataset Structure
@@ -112,14 +110,12 @@ The dataset data is contained in the [data directory](https://huggingface.co/dat
 
 There exists 1 directory per language.
 
-Within those directories, there is a directory named `splits`; it contains 1 file per split:
+Within that directory, there is a directory named `splits`; it contains 1 file per split:
 - `test.tar.gz`
 
-Those `.tar.gz` files contain 2 or more directories:
-- `human`
-- 1 or more directories named after the VITS model being used, ex. `thorsten-vits`
+That `.tar.gz` file contains 1 or more directories, named after the VITS model being used: ex. `thorsten-vits`
 
-Each of these directories contain `.wav` files. Keep in mind that these directories can't be merged as they share most of their file names. An identical file name implies a speaker-voice pair, ex. `human/123.wav` and `thorsten-vits/123.wav`.
+Each of these directories contain `.wav` files. Each `.wav` file is named after the ID of its transcript. Keep in mind that these directories can't be merged as they share their file names. An identical file name implies a speaker-voice pair, ex. `human/123.wav` and `thorsten-vits/123.wav`.
 
 Finally, back to the language directory, it contains 3 metadata files, which are not used in the loaded dataset, but might be useful to researchers:
 - `recording-metadata.csv`
@@ -136,8 +132,8 @@ A sample contains contains an Audio feature `audio`, and a string `label`.
 ```
 {
   'audio': {
-    'path': 'ljspeech-vits/1003119935936341070.wav',
-    'array': array([-0.00048828, -0.00106812, -0.00164795, ..., 0., 0., 0.]),
+    'path': 'ljspeech-vits/1660.wav',
+    'array': array([0.00119019, 0.00109863, 0.00106812, ..., 0., 0., 0.]),
     'sampling_rate': 16000
   },
   'label': 'synthetic'