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Merge pull request #10 from sensein/dev
speech to text works fine
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| Original file line number | Diff line number | Diff line change |
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| """This module implements some utilities for the preprocessing task.""" | ||
| from typing import Any, Dict | ||
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| import torch | ||
| import torchaudio.functional as F | ||
| from datasets import Dataset | ||
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| from senselab.utils.tasks.input_output import _from_dict_to_hf_dataset, _from_hf_dataset_to_dict | ||
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| def resample_hf_dataset(dataset: Dict[str, Any], resample_rate: int, rolloff: float = 0.99) -> Dict[str, Any]: | ||
| """Resamples a Hugging Face `Dataset` object.""" | ||
| hf_dataset = _from_dict_to_hf_dataset(dataset) | ||
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| def _resample_hf_row(row: Dataset, resample_rate: int, rolloff: float = 0.99) -> Dict[str, Any]: | ||
| """Resamples audio data in a hf dataset row. | ||
| A lower rolloff will therefore reduce the amount of aliasing, but it will also reduce some of the higher frequencies. | ||
| """ | ||
| waveform = row['audio']['array'] | ||
| # Ensure waveform is a PyTorch tensor | ||
| if not isinstance(waveform, torch.Tensor): | ||
| waveform = torch.tensor(waveform) | ||
| sampling_rate = row['audio']['sampling_rate'] | ||
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| resampled_waveform = F.resample(waveform, sampling_rate, resample_rate, rolloff=rolloff) | ||
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| return {'audio': {'array': resampled_waveform, 'sampling_rate': resample_rate}} | ||
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| resampled_hf_dataset = hf_dataset.map(lambda x: _resample_hf_row(x, resample_rate, rolloff)) | ||
| return _from_hf_dataset_to_dict(resampled_hf_dataset) |
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| """This module defines a pydra API for the preprocessing task.""" | ||
| import pydra | ||
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| from senselab.audio.tasks.preprocessing import resample_hf_dataset | ||
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| resample_hf_dataset_pt = pydra.mark.task(resample_hf_dataset) |
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