Improve alignment accuracy by normalizing audio features

[IbrahimAmin1]

Audio data should be pre-processed using the Wav2Vec2Processor (Wav2Vec2FeatureExtractor), I have noticed considerable alignment improvement (Mean absolute error) when audio is normalized (zero mean and unit variance) using the processor before the forward pass.

Other than that, Each Hugging face Wav2Vec2 Feature Extractor configuration should contain the same config used during fine-tuning these models (e.g. normalization, attention_mask usage, etc..)

A typical hugging face Wav2Vec2 Feature Extractor config file is as follows:

{
  "do_normalize": true,
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0.0,
  "return_attention_mask": true,
  "sampling_rate": 16000
}

To maintain backwards compatibility, I have opted to let the user determine if Pre-processing should be applied or not, but chose to set Pre-processing as the default option as it improves alignment considerably.

[Barabazs]

Hi @IbrahimAmin1 thank you for the contribution.

Can you provide some examples to compare the result with and without the preprocessing?
Regarding the default behavior, I would suggest to default to False to keep the results consistent with previous versions. Maybe optionally add a CLI flag to activate it?