Wrong dtype for array in audio features
State: open | Author: qmeeus (NONE)

### Describe the bug

When concatenating/interleaving different datasets, I stumble into an error because the features can't be aligned. After some investigation, I understood that the audio arrays had different dtypes, namely `float32` and `float64`. Consequently, the datasets cannot be merged.

### Steps to reproduce the bug

For example, for `facebook/voxpopuli` and `mozilla-foundation/common_voice_11_0`:

```
from datasets import load_dataset, interleave_datasets

covost = load_dataset("mozilla-foundation/common_voice_11_0", "en", split="train", streaming=True)
voxpopuli = datasets.load_dataset("facebook/voxpopuli", "nl", split="train", streaming=True)

sample_cv, = covost.take(1)
sample_vp, = voxpopuli.take(1)

assert sample_cv["audio"]["array"].dtype == sample_vp["audio"]["array"].dtype
# Fails

dataset = interleave_datasets([covost, voxpopuli])

# ValueError: The features can't be aligned because the key audio of features {'audio_id': Value(dtype='string', id=None), 'language': Value(dtype='int64', id=None), 'audio': {'array': Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None), 'path': Value(dtype='string', id=None), 'sampling_rate': Value(dtype='int64', id=None)}, 'normalized_text': Value(dtype='string', id=None), 'gender': Value(dtype='string', id=None), 'speaker_id': Value(dtype='string', id=None), 'is_gold_transcript': Value(dtype='bool', id=None), 'accent': Value(dtype='string', id=None), 'sentence': Value(dtype='string', id=None)} has unexpected type - {'array': Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None), 'path': Value(dtype='string', id=None), 'sampling_rate': Value(dtype='int64', id=None)} (expected either Audio(sampling_rate=16000, mono=True, decode=True, id=None) or Value("null").
```

### Expected behavior

The audio should be loaded to arrays with a unique dtype (I guess `float32`)

### Environment info

```
- `datasets` version: 2.7.1.dev0
- Platform: Linux-4.18.0-425.3.1.el8.x86_64-x86_64-with-glibc2.28
- Python version: 3.9.15
- PyArrow version: 10.0.1
- Pandas version: 1.5.2
```

Comments: After some more investigation, this is due to [this line of code](https://github.com/huggingface/datasets/blob/main/src/datasets/features/audio.py#L279). The function `sf.read(file)` should be updated to `sf.read(file, dtype="float32")`

Indeed, the default value in soundfile is `float64` ([see here](https://pysoundfile.readthedocs.io/en/latest/#soundfile.read)). 


@qmeeus I agree, decoding of different audio formats should return the same dtypes indeed!

But note that here you are concatenating datasets with different sampling rates: 48000 for CommonVoice and 16000 for Voxpopuli. So you should cast them to the same sampling rate value before interleaving, for example:
```
cv = cv.cast_column("audio", Audio(sampling_rate=16000))
```
otherwise you would get the same error because features of the same column ("audio") are not the same.

Also, the error you get is unexpected. Could you please confirm that you use the latest main version of the `datasets`?  We had an issue that could lead to an error like this after using `rename_column` method, but it was fixed in https://github.com/huggingface/datasets/pull/5287 

Hi Polina,
Sorry for the late answer
It is possible that the issue was due to a bug that is now fixed. I installed an editable version of datasets from github, but I don't recall whether I had updated it at the time of the issue. My research led me to other directions so I did not follow through on the interleave datasets.