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USV Detection

DrCoffey edited this page Jan 25, 2019 · 10 revisions

Before vocalizations can be detected, an audio folder, neural network folder, and output folder must be selected.

After detecting calls, we recommend using a post hoc denoising network to remove false positives.

To process a single file:

  1. Set High Precision | High Recall slider

    • When slider is set to high precision, USV detection will be fast and accurate but may miss some quiet calls
    • When slider is set to high recall, USV detection is slightly slower but will detect even extremely low signal, but is more susceptible to noise
    • Default slider position is in the middle, which balances both approaches
  2. Select the desired audio file in the "Audio Files" drop-down menu

  3. Select an appropriate neural network in the "Neural Networks" drop-down menu

  4. Click "Detect Calls"

  5. Enter detection settings as described below, and click "OK"

To process files in a batch, or to process a single file with multiple networks:

  1. Set High Precision | High Recall slider (described above)

  2. Click "Multi Detect"

  3. A list of the audio files in the current folder will appear. Select the desired audio files. Multiple files may be selected by holding the Ctrl key while clicking. Click "OK" to proceed.

  4. After selecting the audio file(s), a box will appear, listing available neural networks. Select a maximum of two, and click "OK".

  5. Enter detection settings as described below, and click "OK".

Detection Settings:

  • Total Analysis Length

    • Length, in seconds, of the audio file to process.

    • Set to 0 to process the entire file

    • If analysis length is greater than the file duration, a warning will be displayed in the command line, and the entire file will be processed

  • Analysis Chunk Length

    • Length of the audio sections to process at a time, in seconds

    • Files are processed in short chunks. The maximum length of each chunk is dependent on available GPU memory, frequency cutoffs, and the neural network

    • We found that a GPU with two gigabytes of memory performs well with three second chunks for short rat and mouse calls, and fifteen second chunks for long rat calls

    • If the GPU runs out of memory, a warning message will be displayed in the command line

  • Overlap

    • Amount of overlap between audio chunks, in seconds

    • Value should be about the length of a call

  • Frequency Cut Off High

    • Regions of the spectrogram above this value are ignored
  • Frequency Cut Off Low

    • Regions of the spectrogram below this value are ignored
  • Score Threshold

    • Detected items with a score (likelihood of being a hit) below this value are automatically set to rejected.
    • Default = 0; All detections will be saved to the detection file
  • Append Date to File Name

    • If value is "1", the detection time will be appended to the end of the file nameof the file name