Keyword Spotting¶

Keyword Spotting vs Speed Recognition¶

Types¶

Challenges¶

Aspect	Constraint	Comment	Metrics
System performance	Latency	Listening animation
	Bandwidth
Preserving	Security	Safeguarding data being sent to cloud
	Privacy
Model	Accuracy	Listen continuously, but only trigger at the right time Pick operating point accordingly
	Personalization	Trigger only for user, not for other users or for background noise
Resource constraints	Battery
	Memory

Model¶

Spectrogram is just an image

TinyConv¶

Since we only we are only focused on recognizing a few keywords, we can just use One Conv2D followed by single dense layer

flowchart LR

Input --> Conv --> FC --> Softmax --> Output

Limitations¶

• Limited vocabulary
• Lower accuracy
• Limited UX

Cascading¶

Multiple Inferences¶

• Average inferences across multiple time slices

This is to avoid False Positives for group of words. For eg: - No - No good - Notion - Notice - Notable

Comments