Wav2Vec2CTCTokenizer does not add blank token between repeated letters
### System Info

- `transformers` version: 4.22.2
- Platform: Linux-5.19.11-arch1-1-x86_64-with-glibc2.36
- Python version: 3.10.0
- Huggingface_hub version: 0.10.0
- PyTorch version (GPU?): 1.12.1+cu102 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no


### Who can help?

@patrickvonplaten, @anton-l

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

When encoding/decoding with `Wav2Vec2CTCTokenizer`, I expect blank tokens between repeated letters. If they are left out, a model will never be able to learn to correctly spell any word with repeated letters.

```python3
import transformers

tokenizer = transformers.Wav2Vec2CTCTokenizer.from_pretrained(
    "facebook/wav2vec2-base-960h"
)

transcription = "ee".upper()

input_ids = tokenizer(text=transcription)['input_ids']
print(input_ids)
print(tokenizer.decode(input_ids))
```

Output:
```
> [5, 5]
> E
```

### Expected behavior

Output should be 
```
> [5, 0, 5]
> EE
```