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Speech Commands Dataset
Load the Speech Commands dataset in Python fast with one line of code. Training and evaluation of keyword detection algorithms. Stream Speech Commands dataset.
Visualization of the Speech commads dataset on the Activeloop Platform

Speech Commands dataset

What is Speech Commands Dataset?

The Speech Commands dataset was created to aid in the training and evaluation of keyword detection algorithms. Its main purpose is to make it easy to create and test simple models that can recognize when a single word is uttered from a list of 10 target words with as few false positives as possible due to background noise or unrelated speech. It's worth noting that the label "unknown" appears far more frequently in the train and validation sets than the labels of the target words or background noise.

Download Speech Commands Dataset in Python

Instead of downloading the Speech Commands dataset in Python, you can effortlessly load it in Python via our open-source package Hub with just one line of code.

Load Speech Commands Dataset Training Subset in Python

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import hub
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ds = hub.load("hub://activeloop/speech-commands-train")
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Load Speech Commands Dataset Testing Subset in Python

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import hub
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ds = hub.load("hub://activeloop/speech-commands-test")
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Speech Commands Dataset Structure

Speech Commands Data Fields

  • audios: tensor containing audios in wav format.
  • labels: tensor representing the category for the audio.

Speech Commands Data Splits

How to use Speech Commands Dataset with PyTorch and TensorFlow in Python

Train a model on Speech Commands dataset with PyTorch in Python

Let's use Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
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dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
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Train a model on Speech Commands dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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Additional Information about Speech Commands Dataset

Speech Commands Dataset Description

  • Repository: N/A
  • Paper: Introduced by P Warden in Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
  • Point of Contact: N/A

Speech Commands Dataset Curators

P Warden

Speech Commands Dataset Licensing Information

Hub users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.
If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

Speech Commands Dataset Citation Information

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

What is the Speech Commands dataset for Python?

A spoken-word audio dataset was created to help with the training and evaluation of keyword detection algorithms. Its main purpose is to make it easy to create and test simple models that can recognize when a single word is uttered from a list of 10 target words with as few false positives as possible due to background noise or unrelated speech.
How to download the Speech Commands dataset in Python?
You can load Speech Commands dataset fast with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to load Speech Commands dataset training subset and testing subset in Python.

How can I use Speech Commands dataset in PyTorch or TensorFlow?

You can stream the Speech Commands dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to train a model on Speech Commands dataset with PyTorch in Python or train a model on Speech Commands dataset with TensorFlow in Python.