Keyphrase detector
A few examples using the Keyword Spotter model to detect over 140 short phrases such as "start game" and "next song." Includes a snake game and a YouTube player that respond to voice commands.
Languages: Python
Audio classification
An audio classification model can recognize sounds or spoken words and phrases.
Currently, all audio classification models that are compatible with the Edge TPU are feed-forward CNN architectures, so they're effective for short audio samples only.
Trained models link
These models are trained and compiled for the Edge TPU.
Notice: These are not production-quality models; they are for demonstration purposes only.
| Model name | Detections/Dataset | Input size | Micro 1 | Model size | Downloads |
|---|---|---|---|---|---|
|
YamNet |
520+ sounds |
15600x1 (WAV) | No | 4.2 MB | |
|
YamNet without frontend |
520+ sounds |
96x64x1 (spectrogram) | Yes | 4.1 MB | |
|
Keyword Spotter v0.7 |
140+ speech phrases |
198x32x1 (spectrogram) | Yes | 578 KB | |
|
Keyword Spotter v0.8 |
140+ speech phrases |
198x32x1 (spectrogram) | Yes | 578 KB |
1 Indicates compatibility with the Dev Board Micro. Some models are not compatible because they require a CPU-bound op that is not supported by TensorFlow Lite for Microcontrollers or they require more memory than available on the board. (All models are compatible with all other Coral boards.)