18367859. SIMULTANEOUS ACOUSTIC EVENT DETECTION ACROSS MULTIPLE ASSISTANT DEVICES simplified abstract (GOOGLE LLC)

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SIMULTANEOUS ACOUSTIC EVENT DETECTION ACROSS MULTIPLE ASSISTANT DEVICES

Organization Name

GOOGLE LLC

Inventor(s)

Matthew Sharifi of Kilchberg (CH)

Victor Carbune of Zurich (CH)

SIMULTANEOUS ACOUSTIC EVENT DETECTION ACROSS MULTIPLE ASSISTANT DEVICES - A simplified explanation of the abstract

This abstract first appeared for US patent application 18367859 titled 'SIMULTANEOUS ACOUSTIC EVENT DETECTION ACROSS MULTIPLE ASSISTANT DEVICES

Simplified Explanation

The patent application describes a system that can detect and process audio data captured by multiple assistant devices in an ecosystem. Here are the key points:

  • The system can detect audio data capturing an acoustic event at multiple assistant devices.
  • Each assistant device processes the audio data locally to generate measures associated with the acoustic event using event detection models.
  • The measures are then processed to determine if the detected acoustic event is an actual event.
  • If the event is determined to be actual, an action associated with the event is performed in response.

Potential applications of this technology:

  • Smart home systems: The system can be used to detect and respond to various acoustic events in a smart home, such as a doorbell ringing or a smoke alarm going off.
  • Voice assistants: The technology can enhance the capabilities of voice assistants by allowing them to detect and respond to specific acoustic events, such as a user saying a wake word or a specific command.
  • Security systems: The system can be integrated into security systems to detect and respond to suspicious acoustic events, such as glass breaking or an alarm sounding.

Problems solved by this technology:

  • Improved accuracy: By processing audio data locally at each assistant device, the system can reduce latency and improve the accuracy of detecting and responding to acoustic events.
  • Privacy concerns: Processing audio data locally ensures that sensitive information is not sent to a central server, addressing privacy concerns associated with audio data collection.

Benefits of this technology:

  • Faster response time: By processing audio data locally, the system can quickly detect and respond to acoustic events, providing a faster and more seamless user experience.
  • Enhanced user privacy: Processing audio data locally reduces the need for sending sensitive information to a central server, ensuring user privacy.
  • Scalability: The system can be deployed across multiple assistant devices in an ecosystem, allowing for scalability and widespread adoption.


Original Abstract Submitted

Implementations can detect respective audio data that captures an acoustic event at multiple assistant devices in an ecosystem that includes a plurality of assistant devices, process the respective audio data locally at each of the multiple assistant devices to generate respective measures that are associated with the acoustic event using respective event detection models, process the respective measures to determine whether the detected acoustic event is an actual acoustic event, and cause an action associated with the actional acoustic event to be performed in response to determining that the detected acoustic event is the actual acoustic event. In some implementations, the multiple assistant devices that detected the respective audio data are anticipated to detect the respective audio data that captures the actual acoustic event based on a plurality of historical acoustic events being detected at each of the multiple assistant devices.

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