Preemptive Wakeword Detection Latency Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing voice interface devices experience latency in processing voice commands due to the time required to detect wakewords, leading to delayed responses and a suboptimal user experience.
Innovation Solution
Implementing a preemptive wakeword detection system that uses wakeword models to analyze audio data for likely wakeword detections, allowing for early initiation of speech processing and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system waits for complete wakeword detection before initiating speech processing, then detection accuracy is improved, but response latency increases
Solution Approach 1:
The system performs preliminary wakeword detection using a lightweight model to identify likely wakeword occurrences before complete detection is available. This preliminary action triggers early initiation of speech processing pipelines, allowing the system to prepare and process audio data in advance, thereby reducing overall response latency while maintaining accurate wakeword recognition through subsequent verification
2Speed
If speech processing is initiated early based on likely wakeword detection, then response speed is improved, but false positive rate increases
Solution Approach 1:
The system implements feedback mechanisms where the results of preliminary wakeword detection are continuously monitored and validated against complete detection outcomes. When false positives are detected, the system adjusts detection thresholds and triggers re-verification processes, allowing early initiation of speech processing while maintaining reliability through iterative validation and correction
Solution Approach 2:
The system performs partial speech processing operations in advance based on likely wakeword detection, rather than waiting for complete confirmation. This partial action includes preliminary audio analysis and command preparation, which can be cancelled or adjusted if false positives are later identified, thereby improving response speed without permanently compromising system reliability
Data Source
AI summary
Systems and methods for preemptive wakeword detection are disclosed. For example, a first part of a wakeword is detected from audio data representing a user utterance. When this occurs, on-device speech processing is initiated prior to when the entire wakeword is detected. When the entire wakeword is detected, results from the on-device speech processing and/or the audio data is sent to a speech processing system to determine a responsive action to be performed by the device. When the entire wakeword is not detected, on-device processing is canceled and the device refrains from sending the audio data to the speech processing system.