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Version: v1.4.0

Dataset format: Audio regression

Dataset format

The data for an audio regression experiment needs to be in a zip file (1) containing a CSV file (2) and an audio folder (3).

folder_name.zip (1)
│ └───csv_name.csv (2)
│ │
│ └───audio_folder_name (3)
│ └───name_of_audio.audio_extension
│ └───name_of_audio.audio_extension
│ └───name_of_audio.audio_extension
│ ...
Note

You can have multiple CSV files in the zip file that you can use as train, validation, and test dataframes:

  • A train CSV file needs to follow the format described above
  • A validation CSV file needs to follow the same format as a train CSV file
  • A test CSV file needs to follow the same format as a train CSV file, but does not require a label column(s)
  1. The available dataset connectors require the data for an audio regression experiment to be in a zip file.
    Note

    To learn how to upload your zip file as your dataset in H2O Hydrogen Torch, see Dataset connectors.

  2. A CSV file containing the following columns:
    • An audio column containing the names of the audios for the experiment, where each audio has an audio extension specified
      Note
      • Audios can contain a mix of supported audio extensions. To learn about supported audio extensions, see Supported audio extensions for audio processing.
      • The names of the audio files do not specify the data directory (location of the audio in the zip file). You can specify the data directory (data folder) when uploading the dataset or before the dataset is used for an experiment. For more information, see Import dataset settings.
    • One or more label columns containing the numerical labels (targets)
      Note

      H2O Hydrogen Torch can train models that predict multiple labels simultaneously. You can provide multiple columns with multiple unique labels and choose which labels to predict when starting an audio regressuin experiment.

    • An optional fold column containing cross-validation fold indexes
      Note

      The fold column can include integers (0, 1, 2, … , N-1 values or 1, 2, 3… , N values) or categorical values.

  3. An audio folder that contains all the audio files specified in the audio column; H2O Hydrogen Torch uses the audios in this folder to run the audio regression experiment.
    Note

    All audio file names need to specify an audio extension. Audios can contain a mix of supported audio extensions. To learn about supported audio extensions, see Supported audio extensions for audio processing.

Example

The amnist_audio_regression.zip file is a preprocessed dataset in H2O Hydrogen Torch and was formatted to solve an audio regression problem. The zip file contains a CSV file and an audio folder. The structure of the zip file is:

amnist_audio_regression.zip
│ └───amnist_meta.csv
│ │
│ └───amnist_audios
│ └───0_01_0.ogg
│ └───0_01_1.ogg
│ └───0_01_2.ogg
│ ...

The first three rows of the CSV file are:

audiolabelfold
2_26_2.ogg20
2_26_38.ogg21
9_26_47.ogg92
Note
  • In this example, the data directory in the audio column is not specified. That being the case, it needs to be specified when uploading the dataset, and the amnist_audios folder needs to be selected as the value for the Data folder setting. For more information, see Import dataset settings.
  • To learn how to access one of the preprocessed datasets in H2O Hydrogen Torch, see Demo (preprocessed) datasets.

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