README.md

metadata

dataset_info:
  features:
    - name: file
      dtype: string
    - name: audio
      struct:
        - name: array
          sequence: float64
        - name: path
          dtype: string
        - name: sampling_rate
          dtype: int64
    - name: text
      dtype: string
    - name: speaker_id
      dtype: int64
    - name: chapter_id
      dtype: int64
    - name: id
      dtype: string
  splits:
    - name: train.clean.100
      num_bytes: 1623641436
      num_examples: 1000
    - name: train.clean.360
      num_bytes: 1572285643
      num_examples: 1000
    - name: train.other.500
      num_bytes: 1502809029
      num_examples: 1000
    - name: validation.clean
      num_bytes: 65591952
      num_examples: 100
    - name: validation.other
      num_bytes: 76760504
      num_examples: 100
    - name: test.clean
      num_bytes: 85852252
      num_examples: 100
    - name: test.other
      num_bytes: 58550856
      num_examples: 100
  download_size: 1181170369
  dataset_size: 4985491672
configs:
  - config_name: default
    data_files:
      - split: train.clean.100
        path: data/train.clean.100-*
      - split: train.clean.360
        path: data/train.clean.360-*
      - split: train.other.500
        path: data/train.other.500-*
      - split: validation.clean
        path: data/validation.clean-*
      - split: validation.other
        path: data/validation.other-*
      - split: test.clean
        path: data/test.clean-*
      - split: test.other
        path: data/test.other-*

Condensed LibriSpeech ASR

This dataset is a condensed version of the LibriSpeech ASR dataset, created by subsampling approximately 10% of the original data from each split. It is intended for quick experimentation, prototyping, and debugging when working with Automatic Speech Recognition (ASR) tasks.

Dataset Details

• Original Dataset: LibriSpeech ASR
• Condensation Ratio: Approximately 10% of the full dataset
• Splits Included:
  • train.clean.100
  • train.clean.360
  • train.other.500
  • validation.clean
  • validation.other
  • test.clean
  • test.other

For each split, a default number of examples was extracted:

• Training Splits: 1,000 examples each
• Validation/Test Splits: 100 examples each

Data Format

Each sample in the dataset contains the following fields:

• file:
  A path to the original audio file (FLAC format).

• audio:
  A dictionary containing:

  • path: Path to the audio file.
  • array: The decoded audio waveform as a NumPy array.
  • sampling_rate: The sampling rate (typically 16 kHz).

• text:
  The transcription corresponding to the audio.

• id:
  A unique identifier for the sample.

• speaker_id:
  A unique identifier for the speaker.

• chapter_id:
  An identifier corresponding to the audiobook chapter.

How Was This Dataset Created?

The condensed dataset was generated by streaming the full LibriSpeech ASR dataset using the Hugging Face Datasets library and selecting approximately 10% of each split. This process preserves the original structure and fields, enabling seamless use with models and workflows designed for LibriSpeech.

Usage Example

Below is a Python snippet to load and inspect the dataset:

from datasets import load_dataset

# Load the condensed dataset from the Hugging Face Hub
dataset = load_dataset("nyalpatel/condensed_librispeech_asr")

# Access a specific split (e.g., test.clean)
test_dataset = dataset["test.clean"]

# Display the first example in the test set
print(test_dataset[0])