10 datasets found
  1. h

    LibriSpeech

    • huggingface.co
    Updated Nov 20, 2023
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    Wilson Wang (2023). LibriSpeech [Dataset]. https://huggingface.co/datasets/ginger-turmeric/LibriSpeech
    Explore at:
    Dataset updated
    Nov 20, 2023
    Authors
    Wilson Wang
    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

  2. h

    librispeech_test_only

    • huggingface.co
    Updated Apr 20, 2023
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    Andrea Gasparini (2023). librispeech_test_only [Dataset]. https://huggingface.co/datasets/andreagasparini/librispeech_test_only
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    Dataset updated
    Apr 20, 2023
    Authors
    Andrea Gasparini
    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

  3. h

    partial-asr

    • huggingface.co
    Updated Oct 19, 2023
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    Omar Cobas (2023). partial-asr [Dataset]. https://huggingface.co/datasets/omarc/partial-asr
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    Dataset updated
    Oct 19, 2023
    Authors
    Omar Cobas
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

  4. T

    librispeech

    • tensorflow.org
    • opendatalab.com
    • +2more
    Updated Dec 11, 2024
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    (2024). librispeech [Dataset]. https://www.tensorflow.org/datasets/catalog/librispeech
    Explore at:
    Dataset updated
    Dec 11, 2024
    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.

    It's recommended to use lazy audio decoding for faster reading and smaller dataset size: - install tensorflow_io library: pip install tensorflow-io - enable lazy decoding: tfds.load('librispeech', builder_kwargs={'config': 'lazy_decode'})

    To use this dataset:

    import tensorflow_datasets as tfds
    
    ds = tfds.load('librispeech', split='train')
    for ex in ds.take(4):
     print(ex)
    

    See the guide for more informations on tensorflow_datasets.

  5. h

    librispeech_asr-timestamped

    • huggingface.co
    Updated Feb 3, 2024
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    Whisper Distillation (2024). librispeech_asr-timestamped [Dataset]. https://huggingface.co/datasets/distil-whisper/librispeech_asr-timestamped
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    Dataset updated
    Feb 3, 2024
    Dataset authored and provided by
    Whisper Distillation
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

  6. h

    librispeech_asr_clean

    • huggingface.co
    Updated Apr 12, 2023
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    Rohit Prasad (2023). librispeech_asr_clean [Dataset]. https://huggingface.co/datasets/rohitp1/librispeech_asr_clean
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    Dataset updated
    Apr 12, 2023
    Authors
    Rohit Prasad
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

  7. h

    librispeech_asr_test

    • huggingface.co
    Updated Apr 28, 2022
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    Hosung Park (2022). librispeech_asr_test [Dataset]. https://huggingface.co/datasets/kresnik/librispeech_asr_test
    Explore at:
    Dataset updated
    Apr 28, 2022
    Authors
    Hosung Park
    Description


    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the .map() function as follows: python import soundfile as sf def map_to_array(batch): speech_array, _ = sf.read(batch["file"]) batch["speech"] = speech_array return batch dataset = dataset.map(map_to_array, remove_columns=["file"])

  8. h

    librispeech_asr_adversarial

    • huggingface.co
    Updated Sep 19, 2022
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    Raphael Olivier (2022). librispeech_asr_adversarial [Dataset]. https://huggingface.co/datasets/RaphaelOlivier/librispeech_asr_adversarial
    Explore at:
    Dataset updated
    Sep 19, 2022
    Authors
    Raphael Olivier
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the .map() function as follows: python import soundfile as sf def map_to_array(batch): speech_array, _ = sf.read(batch["file"]) batch["speech"] = speech_array return batch dataset = dataset.map(map_to_array, remove_columns=["file"])

  9. h

    librispeech_local

    • huggingface.co
    Updated Jan 3, 2022
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    Patrick von Platen (2022). librispeech_local [Dataset]. https://huggingface.co/datasets/patrickvonplaten/librispeech_local
    Explore at:
    Dataset updated
    Jan 3, 2022
    Authors
    Patrick von Platen
    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

    Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the .map() function as follows:

    import soundfile as sf
    
    def map_to_array(batch):
      speech_array, _ = sf.read(batch["file"])
      batch["speech"] = speech_array
      return batch
    
    dataset = dataset.map(map_to_array, remove_columns=["file"])
    
  10. h

    librispeech_asr_dummy

    • huggingface.co
    Updated Dec 22, 2022
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    Patrick von Platen (2022). librispeech_asr_dummy [Dataset]. https://huggingface.co/datasets/patrickvonplaten/librispeech_asr_dummy
    Explore at:
    Dataset updated
    Dec 22, 2022
    Authors
    Patrick von Platen
    Description

    LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.

    Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the .map() function as follows:

    import soundfile as sf
    
    def map_to_array(batch):
      speech_array, _ = sf.read(batch["file"])
      batch["speech"] = speech_array
      return batch
    
    dataset = dataset.map(map_to_array, remove_columns=["file"])
    
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Share
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Wilson Wang (2023). LibriSpeech [Dataset]. https://huggingface.co/datasets/ginger-turmeric/LibriSpeech

LibriSpeech

ginger-turmeric/LibriSpeech

Explore at:
Dataset updated
Nov 20, 2023
Authors
Wilson Wang
Description

LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.87

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