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from speechbox import PunctuationRestorer
from datasets import load_dataset
streamed_dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
# get first sample
sample = next(iter(streamed_dataset))
# print out normalized transcript
print(sample["text"])
# => "HE WAS IN A FEVERED STATE OF MIND OWING TO THE BLIGHT HIS WIFE'S ACTION THREATENED TO CAST UPON HIS ENTIRE FUTURE"
# load the restoring class
restorer = PunctuationRestorer.from_pretrained("openai/whisper-tiny.en")
restorer.to("cuda")
restored_text, log_probs = restorer(sample["audio"]["array"], sample["text"], sampling_rate=sample["audio"]["sampling_rate"], num_beams=1)
print("Restored text:\n", restored_text) |