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license: cc-by-nc-sa-4.0
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This dataset contains precomputed audio features designed for use with the [openWakeWord library](https://github.com/dscripka/openWakeWord).
Specifically, they are intended to be used as general purpose negative data (that is, data that does *not* contain the target wake word/phrase) for training custom openWakeWord models.

The individual .npy files in this dataset are not original audio data, but rather are low dimensional audio features produced by a pre-trained [speech embedding model from Google](https://tfhub.dev/google/speech_embedding/1).
openWakeWord uses these features as inputs to custom word/phrase detection models.

The dataset currently contains precomputed features from the following datasets.

## ACAV100M

The ACAV100M dataset contains a highly diverse set of audio data with multilingual speech, noise, music, all captured in real-world environments.
This is a highly effective dataset for training custom openwakeword models.

**Dataset source**: https://acav100m.github.io/

**Size**: An array of shape (2812500, 16, 96), corresponding to ~1000 hours of audio from the ACAV100M dataset. Each row in the array has a temporal dimension of 16, which at 80 ms per temporal step results in each row containing features representing 1.28 seconds of audio.