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metadata
dataset_info:
  features:
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
    - name: text
      dtype: string
  splits:
    - name: train
      num_bytes: 689300787.16
      num_examples: 11868
    - name: test
      num_bytes: 168022373.81678608
      num_examples: 2927
  download_size: 821530354
  dataset_size: 857323160.976786
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

ATC Dataset - Fine-Tuning Whisper

This dataset was created to fine-tune OpenAI's Whisper model for improving transcription accuracy in Air Traffic Control (ATC) communications. The dataset contains transcriptions and corresponding audio files from two main sources: ATCO2 and the UWB-ATCC corpus, specifically selected for aviation-related communications. The dataset is publicly available on Hugging Face for use in Automatic Speech Recognition (ASR) projects.

For more details on the fine-tuning process, check out the blog post and the corresponding GitHub repository.

Dataset Overview

  • Dataset Name: ATC Dataset
  • Total Samples: 11.9k (Training), 2.93k (Test)
  • Data Sources:
  • Format: Audio files (WAV format) with corresponding transcriptions.
  • The Transciption Ground Truth is within the text column.
  • The Audio Ground Truth is within the audio column.
  • License: MIT

This dataset is particularly useful for training speech recognition models like Whisper on short, domain-specific audio transmissions, such as those between pilots and air traffic controllers.

Key Features

  • Domain-specific: Tailored to ATC communications with specialized phraseology and terms.
  • Diverse accents: Contains multiple accent variations to reflect real-world international aviation communication.
  • Cleaned Data: Includes only high-quality samples after filtering erroneous or incomplete transcriptions.

Usage

  1. Install Dependencies:
    Use Hugging Face's datasets library to load the dataset:

    from datasets import load_dataset
dataset = load_dataset("jacktol/atc-dataset")

  2. Training:
    The dataset is ready for speech recognition tasks such as fine-tuning Whisper models. It includes training and test splits to evaluate models based on Word Error Rate (WER).

License

This dataset is shared under the MIT License. You are free to use, modify, and distribute it as long as you provide proper attribution.