[Whisper] Fix multilingual tokeniser
# What does this PR do?

Fixes #20703

## Before submitting
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- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts and @NielsRogge
- speech models: @sanchit-gandhi

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

Integrations:

- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger and @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
- TensorFlow: @Rocketknight1

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The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20707). All of your documentation changes will be reflected on that endpoint.<|||||>This looks good, could you also push the normalizer file? 😉 <|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>Hi, when we can expect this to be merged? The wrong normalisation basically makes everything that Whisper models gives from languages other than English useless. Thanks<|||||>Hey, no real timeline. Was dropped as this was not requested. If you really need this however, feel free to take the PR over ! 🤗 <|||||>Hey @thomas-ferraz,

What you can do as a temporary workaround is set `_normalize=False` when you decode with the tokenizer (the default behaviour:
```python
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
```
If you don't need normalisation, you can stop here - your transcriptions won't be normalised.

If you need normalisation, you can manually normalise using the `BasicTextNormalizer` (the **multilingual** normaliser) as follows:

```python
from transformers.models.whisper.english_normalizer import BasicTextNormalizer

normalizer = BasicTextNormalizer()
norm_transcriptions = [normalizer(input_str) for input_str in transcription]
```

Hope that helps!<|||||>This should definitely be re-opened and merged. <|||||>Will take a look when I get the chance!