chunked/nltk_chunking/tasks_asr/chunk_3.txt

from datasets import load_dataset, Audio
minds = load_dataset("PolyAI/minds14", name="en-US", split="train[:100]")

Split the dataset's train split into a train and test set with the [~Dataset.train_test_split] method:

minds = minds.train_test_split(test_size=0.2)

Then take a look at the dataset:

minds
DatasetDict({
    train: Dataset({
        features: ['path', 'audio', 'transcription', 'english_transcription', 'intent_class', 'lang_id'],
        num_rows: 16
    })
    test: Dataset({
        features: ['path', 'audio', 'transcription', 'english_transcription', 'intent_class', 'lang_id'],
        num_rows: 4
    })
})

While the dataset contains a lot of useful information, like lang_id and english_transcription, you'll focus on the audio and transcription in this guide.