task_categories:automatic-speech-recognition language:en license:cc-by-4.0 region:us
The People's Speech is a free-to-download 30,000-hour and growing supervised 
conversational English speech recognition dataset licensed for academic and 
commercial usage under CC-BY-SA (with a CC-BY subset).
@article{DBLP:journals/corr/abs-2111-09344,
  author    = {Daniel Galvez and
               Greg Diamos and
               Juan Ciro and
               Juan Felipe Ceron and
               Keith Achorn and
               Anjali Gopi and
               David Kanter and
               Maximilian Lam and
               Mark Mazumder and
               Vijay Janapa Reddi},
  title     = {The People's Speech: A Large-Scale Diverse English Speech Recognition
               Dataset for Commercial Usage},
  journal   = {CoRR},
  volume    = {abs/2111.09344},
  year      = {2021},
  url       = {https://arxiv.org/abs/2111.09344},
  eprinttype = {arXiv},
  eprint    = {2111.09344},
  timestamp = {Mon, 22 Nov 2021 16:44:07 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2111-09344.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: People's Speech Clean
---

# Distil Whisper: People's Speech Clean With Timestamps

This is a variant of the [People's Speech Clean](https://huggingface.co/datasets/MLCommons/peoples_speech) dataset, augmented to return the pseudo-labelled Whisper 
Transcriptions alongside the original dataset elements. The pseudo-labelled transcriptions were generated by 
labelling the input audio data with the Whisper [large-v2](https://huggingface.co/openai/whisper-large-v2)
model with *greedy* sampling and timestamp prediction. For information on how the original dataset was curated, refer to the original 
[dataset card](https://huggingface.co/datasets/MLCommons/peoples_speech).

## Standalone Usage

First, install the latest version of the 🤗 Datasets package:

```bash
pip install --upgrade pip
pip install --upgrade datasets[audio]
```

The dataset can be downloaded and pre-processed on disk using the [`load_dataset`](https://huggingface.co/docs/datasets/v2.14.5/en/package_reference/loading_methods#datasets.load_dataset) 
function:

```python
from datasets import load_dataset

dataset = load_dataset("distil-whisper/peoples_speech-clean", "clean")
# take the first sample of the validation set
sample = dataset["validation"][0]
```

It can also be streamed directly from the Hub using Datasets' [streaming mode](https://huggingface.co/blog/audio-datasets#streaming-mode-the-silver-bullet).
Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire 
dataset to disk:

```python
from datasets import load_dataset

dataset = load_dataset("distil-whisper/peoples_speech-clean", "clean", streaming=True)
# take the first sample of the validation set
sample = next(iter(dataset["validation"]))
```

## Distil Whisper Usage

To use this dataset to reproduce a Distil Whisper training run, refer to the instructions on the 
[Distil Whisper repository](https://github.com/huggingface/distil-whisper#training).

## License

This dataset is licensed under cc-by-4.0.

