davidscripka
commited on
Commit
•
9da9bd4
1
Parent(s):
13d074c
Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,19 @@
|
|
1 |
---
|
2 |
license: cc-by-nc-sa-4.0
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
license: cc-by-nc-sa-4.0
|
3 |
---
|
4 |
+
|
5 |
+
This dataset contains precomputed audio features designed for use with the [openWakeWord library](https://github.com/dscripka/openWakeWord).
|
6 |
+
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.
|
7 |
+
|
8 |
+
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).
|
9 |
+
openWakeWord uses these features as inputs to custom word/phrase detection models.
|
10 |
+
|
11 |
+
The dataset currently contains precomputed features from the following datasets.
|
12 |
+
|
13 |
+
## ACAV100M
|
14 |
+
|
15 |
+
The ACAV100M dataset contains a highly diverse set of audio data with multilingual speech, noise, music, all captured in real-world environments.
|
16 |
+
This is a highly effective dataset for training custom openwakeword models.
|
17 |
+
|
18 |
+
Dataset source: https://acav100m.github.io/
|
19 |
+
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.
|