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Speech Commands Dataset

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Visualization of the Speech commads dataset in the Deep Lake UI

Speech Command dataset

What is Speech CommandDataset?

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 Command Dataset in Python

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

Load Speech Command Dataset Training Subset in Python

import deeplake
ds = deeplake.load("hub://activeloop/speech-commands-train")

Load Speech Command Dataset Testing Subset in Python

import deeplake
ds = deeplake.load("hub://activeloop/speech-commands-test")

Speech Command Dataset Structure

Speech Command Data Fields
  • audios: tensor containing audios in wave format.
  • labels: tensor representing the category for the audio.
Speech Command Data Splits

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

Train a model on the Speech Command dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
Train a model on the Speech Command dataset with TensorFlow in Python
dataloader = ds.tensorflow()

Additional Information about Speech Command Dataset

Speech Command Dataset Description

  1. Homepage:https://arxiv.org/abs/1804.03209
  2. Repository: N/A
  3. Paper: Introduced by P Warden in Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
  4. Point of Contact: N/A
Speech Command Dataset Curators

P Warden

Speech Command Dataset Licensing Information

Deep Lake 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 Command Citation Information
@article{lecun2010mnist,
  title={MNIST handwritten digit database},
  author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
  journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
  volume={2},
  year={2010}
}

Speech Command Dataset FAQs

What is the Speech Command 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 Command dataset in Python?

You can load the Speech Commands dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load the Speech Commands dataset training subset and testing subset in Python.

How can I use the Speech Command 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 Deep Lake 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.

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