---
    license: cc-by-4.0
    task_categories:
      - audio-classification
      - automatic-speech-recognition
    tags:
      - speech-commands
      - keyword-spotting
      - audio
    configs:
      - config_name: default
        data_files:
          - split: train
            path: data/train/**
          - split: validation
            path: data/validation/**
          - split: test
            path: data/test/**
    ---

    # Speech Commands (v0.02)

    One-second WAV clips of spoken words and background noise, organised by
    split and label in the Hugging Face **audiofolder** convention.

    ## Quick start

    ```python
    from datasets import load_dataset

    ds = load_dataset("odunola/speech-commands")
    print(ds)
    ```

    ## Structure

    ```
    data/
      <split>/
        metadata.csv        # file_name, label, is_unknown, speaker_id, utterance_id
        <label>/*.wav
    ```

    ## Labels (36)

    `_silence_`, `backward`, `bed`, `bird`, `cat`, `dog`, `down`, `eight`, `five`, `follow`, `forward`, `four`, `go`, `happy`, `house`, `learn`, `left`, `marvin`, `nine`, `no`, `off`, `on`, `one`, `right`, `seven`, `sheila`, `six`, `stop`, `three`, `tree`, `two`, `up`, `visual`, `wow`, `yes`, `zero`

    ## Source

    - Homepage: https://www.tensorflow.org/datasets/catalog/speech_commands
    - License: Creative Commons BY 4.0 License

    ## Citation

    ```bibtex
    @article{speechcommandsv2,
   author  = {{Warden}, P.},
   title   = "{Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition}",
   journal = {ArXiv e-prints},
   archivePrefix = "arXiv",
   eprint  = {1804.03209},
   primaryClass = "cs.CL",
   year    = 2018,
   month   = apr,
   url     = {https://arxiv.org/abs/1804.03209},
}
    ```

    ## Description

    A set of one-second .wav audio files, each containing a single spoken English word or background noise. These words are from a small set of commands, spoken by a variety of different speakers. Version 0.02 adds the words: backward, forward, follow, learn, visual.