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Wake word detection

As explained in Natural Language Processing in Action, Second Edition

Wake word detection is the automatic identification of a designated spoken phrase that activates a voice assistant.

Wake word detection automatically identifies a designated spoken phrase that activates a voice assistant. It bridges always-listening audio and the assistant’s conversational behavior. section 12.7.4

Effective wake word detection involves more than recognizing words:

  • It must detect the wake-up command efficiently and accurately while the assistant waits for user input. section 12.7.4
  • A robust implementation may require low-level operating-system access and hardware-driver access. section 12.7.4
  • End-to-end voice-assistant platforms can avoid building every low-level component independently. section 12.7.4

A local voice assistant

Mycroft combines speech-to-text, chatbot, and text-to-speech engines locally on Linux computers, including a Raspberry Pi, providing a practical platform for experimenting with wake word activation. section 12.7.4

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Identifies operating-system and hardware-driver demands but stops short of implementation details.
Examples
Uses Mycroft running locally on Linux or a Raspberry Pi as an end-to-end voice-assistant example.
What it assumes
Assumes familiarity with voice assistants and speech-to-text while deferring low-level implementation knowledge.
What you can do after
Evaluate the engineering demands of wake word detection and choose an end-to-end platform for experimentation.
How it connects
Connects wake word detection with speech-to-text, chatbots, text-to-speech, and voice assistants.
Cover of Natural Language Processing in Action, Second Edition
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.