Training corpus summary

projection of the training data. Each dot is one window of audio (explanation below). Hover a dot to hear the sound; click to open the recorded sample.

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LabelDurationOccupancySamplesFragmentsFragment durations0.5s bins Β· hover for countsWindowsWindow durations0.1s bins Β· hover for counts
bark1–3 s50–80 %00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
yap1–3 s50–80 %00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
background3–5 sn/a00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
wind3–5 sn/a00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
homestead3–5 sn/a00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
traffic3–5 sn/a00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
wildlife1–3 s50–80 %00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
gunshot1–3 s50–80 %00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}
wrongdog1–3 s50–80 %00{b:0,0,0,0,0,0,0,0,0,0,0}β€”{b:0,0,0,0,0,0,0,0,0,0,0}

Desired number of fragments: <30 not enough Β· 30–99 viable Β· 100+ good

Hover the table row above to highlight the dots in scatterplot. Click to select.

Each dot is a window. What are YAMNet windows and how are they made?

Explanation of how labelled fragments are divided into embedding windows

Learn more about YAMNET windows