add requirements, change order in readme

README.md

@@ -22,18 +22,9 @@ This dataset downloads LibriTTS and preprocesses it on your machine to create al
 You need to run ``pip install alignments phones`` before using this dataset.
 When running this the first time, it can take an hour or two, but subsequent runs will be lightning fast.
 
-## Splits
-
-This dataset has the following splits:
-- ``train``: All the training data, except one sample per speaker which is used for validation.
-- ``dev``: The validation data, one sample per speaker.
-- ``train.clean.100``: Training set derived from the original materials of the train-clean-100 subset of LibriSpeech.
-- ``train.clean.360``: Training set derived from the original materials of the train-clean-360 subset of LibriSpeech.
-- ``train.other.500``: Training set derived from the original materials of the train-other-500 subset of LibriSpeech.
-- ``dev.clean``: Validation set derived from the original materials of the dev-clean subset of LibriSpeech.
-- ``dev.other``: Validation set derived from the original materials of the dev-other subset of LibriSpeech.
-- ``test.clean``: Test set derived from the original materials of the test-clean subset of LibriSpeech.
-- ``test.other``: Test set derived from the original materials of the test-other subset of LibriSpeech.
+## Requirements
+- ``pip install alignments phones`` **(required)**
+- ``pip install speech-collator`` (optional)
 
 ## Example Item
 
@@ -52,14 +43,6 @@ This dataset has the following splits:
 
 The phones are IPA phones, and the phone durations are in frames (assuming a hop length of 256, sample rate of 22050 and window length of 1024). These attributes can be changed using the ``hop_length``, ``sample_rate`` and ``window_length`` arguments to ``LibriTTSAlign``.
 
-## Environment Variables
-
-There are a few environment variable which can be set.
-
-- ``LIBRITTS_VERBOSE``: If set, will print out more information about the dataset creation process.
-- ``LIBRITTS_MAX_WORKERS``: The number of workers to use when creating the alignments. Defaults to ``cpu_count()``.
-- ``LIBRITTS_PATH``: The path to download LibriTTS to. Defaults to the value of ``HF_DATASETS_CACHE``.
-
 ## Data Collator
 
 This dataset comes with a data collator which can be used to create batches of data for training.
@@ -127,6 +110,27 @@ dataloader = DataLoader(dataset, collate_fn=collator.collate_fn, batch_size=8)
 
 COMING SOON: Detailed documentation on how to use the measures at [MiniXC/speech-collator](https://www.github.com/MiniXC/speech-collator).
 
+## Splits
+
+This dataset has the following splits:
+- ``train``: All the training data, except one sample per speaker which is used for validation.
+- ``dev``: The validation data, one sample per speaker.
+- ``train.clean.100``: Training set derived from the original materials of the train-clean-100 subset of LibriSpeech.
+- ``train.clean.360``: Training set derived from the original materials of the train-clean-360 subset of LibriSpeech.
+- ``train.other.500``: Training set derived from the original materials of the train-other-500 subset of LibriSpeech.
+- ``dev.clean``: Validation set derived from the original materials of the dev-clean subset of LibriSpeech.
+- ``dev.other``: Validation set derived from the original materials of the dev-other subset of LibriSpeech.
+- ``test.clean``: Test set derived from the original materials of the test-clean subset of LibriSpeech.
+- ``test.other``: Test set derived from the original materials of the test-other subset of LibriSpeech.
+
+## Environment Variables
+
+There are a few environment variable which can be set.
+
+- ``LIBRITTS_VERBOSE``: If set, will print out more information about the dataset creation process.
+- ``LIBRITTS_MAX_WORKERS``: The number of workers to use when creating the alignments. Defaults to ``cpu_count()``.
+- ``LIBRITTS_PATH``: The path to download LibriTTS to. Defaults to the value of ``HF_DATASETS_CACHE``.
+
 # Citation
 
 When using LibriTTS please cite the following papers: