README.md

metadata

license: cc-by-4.0
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: name
      dtype: string

LibriSpeech: An ASR corpus based on public domain audio books

This is a mirror of the LibriSpeech ASR corpus. The original files were converted from FLAC to Opus to reduce the size and accelerate streaming. The transcripts are not included. This mirror is thus best suited for audio-to-audio tasks.

• Sampling rate: 16 kHz
• Channels: 1
• Format: Opus
• Splits:
  • Train: 460 hours, 132553 utterances, train-clean-100 and train-clean-360 sets.
  • Validation: 7 hours, 2703 utterances, dev-clean set.
  • Test: 7 hours, 2620 utterances, test-clean set.
• License: CC BY 4.0
• Source: https://www.openslr.org/12
• Paper: Librispeech: An ASR corpus based on public domain audio books

Usage

import io

import soundfile as sf
from datasets import Features, Value, load_dataset

for item in load_dataset(
    "philgzl/libri",
    split="train",
    streaming=True,
    features=Features({"audio": Value("binary"), "name": Value("string")}),
):
    print(item["name"])
    buffer = io.BytesIO(item["audio"])
    x, fs = sf.read(buffer)
    # do stuff...

Citation

@inproceedings{panayotov2015librispeech,
  title = {{LibriSpeech}: {An} {ASR} corpus based on public domain audio books},
  author = {Panayotov, Vassil and Chen, Guoguo and Povey, Daniel and Khudanpur, Sanjeev},
  booktitle = {Proc. ICASSP},
  pages = {5206--5210},
  year = {2015},
}