.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorials/audio_datasets_tutorial.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_tutorials_audio_datasets_tutorial.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_tutorials_audio_datasets_tutorial.py:


Audio Datasets
==============

**Author**: `Moto Hira <moto@meta.com>`__

``torchaudio`` provides easy access to common, publicly accessible
datasets. Please refer to the official documentation for the list of
available datasets.

.. GENERATED FROM PYTHON SOURCE LINES 12-23

.. code-block:: default


    # When running this tutorial in Google Colab, install the required packages
    # with the following.
    # !pip install torchaudio

    import torch
    import torchaudio

    print(torch.__version__)
    print(torchaudio.__version__)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    1.13.0
    0.13.0




.. GENERATED FROM PYTHON SOURCE LINES 24-27

Preparing data and utility functions (skip this section)
--------------------------------------------------------


.. GENERATED FROM PYTHON SOURCE LINES 27-77

.. code-block:: default


    # @title Prepare data and utility functions. {display-mode: "form"}
    # @markdown
    # @markdown You do not need to look into this cell.
    # @markdown Just execute once and you are good to go.

    # -------------------------------------------------------------------------------
    # Preparation of data and helper functions.
    # -------------------------------------------------------------------------------
    import os

    import matplotlib.pyplot as plt
    from IPython.display import Audio, display


    _SAMPLE_DIR = "_assets"
    YESNO_DATASET_PATH = os.path.join(_SAMPLE_DIR, "yes_no")
    os.makedirs(YESNO_DATASET_PATH, exist_ok=True)


    def plot_specgram(waveform, sample_rate, title="Spectrogram", xlim=None):
        waveform = waveform.numpy()

        num_channels, _ = waveform.shape

        figure, axes = plt.subplots(num_channels, 1)
        if num_channels == 1:
            axes = [axes]
        for c in range(num_channels):
            axes[c].specgram(waveform[c], Fs=sample_rate)
            if num_channels > 1:
                axes[c].set_ylabel(f"Channel {c+1}")
            if xlim:
                axes[c].set_xlim(xlim)
        figure.suptitle(title)
        plt.show(block=False)


    def play_audio(waveform, sample_rate):
        waveform = waveform.numpy()

        num_channels, _ = waveform.shape
        if num_channels == 1:
            display(Audio(waveform[0], rate=sample_rate))
        elif num_channels == 2:
            display(Audio((waveform[0], waveform[1]), rate=sample_rate))
        else:
            raise ValueError("Waveform with more than 2 channels are not supported.")









.. GENERATED FROM PYTHON SOURCE LINES 78-81

Here, we show how to use the
:py:class:`torchaudio.datasets.YESNO` dataset.


.. GENERATED FROM PYTHON SOURCE LINES 81-89

.. code-block:: default



    dataset = torchaudio.datasets.YESNO(YESNO_DATASET_PATH, download=True)

    for i in [1, 3, 5]:
        waveform, sample_rate, label = dataset[i]
        plot_specgram(waveform, sample_rate, title=f"Sample {i}: {label}")
        play_audio(waveform, sample_rate)



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /tutorials/images/sphx_glr_audio_datasets_tutorial_001.png
         :alt: Sample 1: [0, 0, 0, 1, 0, 0, 0, 1]
         :srcset: /tutorials/images/sphx_glr_audio_datasets_tutorial_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /tutorials/images/sphx_glr_audio_datasets_tutorial_002.png
         :alt: Sample 3: [0, 0, 1, 0, 0, 0, 1, 0]
         :srcset: /tutorials/images/sphx_glr_audio_datasets_tutorial_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /tutorials/images/sphx_glr_audio_datasets_tutorial_003.png
         :alt: Sample 5: [0, 0, 1, 0, 0, 1, 1, 1]
         :srcset: /tutorials/images/sphx_glr_audio_datasets_tutorial_003.png
         :class: sphx-glr-multi-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


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    100%|##########| 4.49M/4.49M [00:00<00:00, 5.80MB/s]
    <IPython.lib.display.Audio object>
    <IPython.lib.display.Audio object>
    <IPython.lib.display.Audio object>





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  2.048 seconds)


.. _sphx_glr_download_tutorials_audio_datasets_tutorial.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example


    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: audio_datasets_tutorial.py <audio_datasets_tutorial.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: audio_datasets_tutorial.ipynb <audio_datasets_tutorial.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_