cast_column function not working with map function in streaming mode for Audio features
Hi! This is probably due to the fact that `IterableDataset.map` sets `features` to `None` before mapping examples. We can fix the issue by passing the old `features` dict to the map generator and performing encoding/decoding there (before calling the map transform function).
## Describe the bug
I am trying to use Audio class for loading audio features using custom dataset. I am able to cast 'audio' feature into 'Audio' format with cast_column function. On using map function, I am not getting 'Audio' casted feature but getting path of audio file only.
I am getting features of 'audio' of string type with load_dataset call. After using cast_column 'audio' feature is converted into 'Audio' type. But in map function I am not able to get Audio type for audio feature & getting string type data containing path of file only. So I am not able to use processor in encode function.

## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from datasets import load_dataset, Audio
from transformers import Wav2Vec2Processor

def encode(batch, processor):
    print("Audio: ",batch['audio'])
    batch["input_values"] = processor(batch["audio"]['array'], sampling_rate=16000).input_values
    return batch

def print_ds(ds):
    iterator = iter(ds)
    for d in iterator:
        print("Data: ",d)
        break

processor = Wav2Vec2Processor.from_pretrained(pretrained_model_path)

dataset = load_dataset("custom_dataset.py","train",data_files={'train':'train_path.txt'},
                                data_dir="data", streaming=True, split="train")

print("Features: ",dataset.features)

print_ds(dataset)

dataset = dataset.cast_column("audio", Audio(sampling_rate=16_000))

print("Features: ",dataset.features)

print_ds(dataset)

dataset = dataset.map(lambda x: encode(x,processor))

print("Features: ",dataset.features)

print_ds(dataset)



```

## Expected results

map function not printing Audio type features be used with processor function and getting error in processor call due to this.

## Actual results

# after load_dataset call
Features:  {'sentence': Value(dtype='string', id=None), 'audio': Value(dtype='string', id=None)}
Data:  {'sentence': 'और अपने पेट को माँ की स्वादिष्ट गरमगरम जलेबियाँ हड़पते\n', 'audio': 'data/0116_003.wav'}

# after cast_column call
Features:  {'sentence': Value(dtype='string', id=None), 'audio': Audio(sampling_rate=16000, mono=True, _storage_dtype='string', id=None)}
Data:  {'sentence': 'और अपने पेट को माँ की स्वादिष्ट गरमगरम जलेबियाँ हड़पते\n', 'audio': {'path': 'data/0116_003.wav', 'array': array([ 1.2662281e-06,  1.0264218e-06, -1.3615092e-06, ...,
        1.3017889e-02,  1.0085563e-02,  4.8155054e-03], dtype=float32), 'sampling_rate': 16000}}

# after map call
Features:  None
Audio:  data/0116_003.wav

Traceback (most recent call last):
  File "demo2.py", line 36, in <module>
    print_ds(dataset)
  File "demo2.py", line 11, in print_ds
    for d in iterator:
  File "/opt/conda/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 341, in __iter__
    for key, example in self._iter():
  File "/opt/conda/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 338, in _iter
    yield from ex_iterable
  File "/opt/conda/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 192, in __iter__
    yield key, self.function(example)
  File "demo2.py", line 32, in <lambda>
    dataset = dataset.map(lambda x: batch_encode(x,processor))
  File "demo2.py", line 6, in batch_encode
    batch["input_values"] = processor(batch["audio"]['array'], sampling_rate=16000).input_values
TypeError: string indices must be integers
## Environment info

- `datasets` version: 1.17.0
- Platform: Linux-4.14.243 with-debian-bullseye-sid
- Python version: 3.7.9
- PyArrow version: 6.0.1
