Digital Assistant Trigger Detection Using Multi-Microphone Segmentation
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Solution Overview
Problem
Digital assistants face challenges in accurately detecting spoken triggers due to interfering audio signals and distinguishing relevant user inputs from irrelevant noise, leading to inefficient user experiences and incorrect session initiations.
Innovation Solution
The method involves sampling audio signals from multiple microphones to process multiple audio streams, determining if a spoken trigger is present, and initiating or foregoing a digital assistant session based on these signals, using a centralized device with the highest processing power to analyze and interpret the audio data accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio signals are sampled from multiple microphones to improve detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The audio detection process is segmented into distinct stages: initial trigger detection using a first microphone, followed by verification using a second microphone. This segmentation allows the system to maintain high detection accuracy while avoiding the continuous complexity of processing all microphones simultaneously, as each microphone is activated only when needed in the detection sequence.
2Speed
If audio signals are continuously monitored to improve response time, then speed is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic action by continuously monitoring audio signals for trigger patterns and only activating the full multi-microphone verification process when a potential trigger is detected. During normal operation, the system uses lower-power monitoring, and only transitions to higher-power verification mode periodically when necessary, thus maintaining fast response times while reducing overall energy consumption compared to continuous full-power monitoring.
3Measurement precision
If multiple audio streams are processed to distinguish user input from noise, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system applies preliminary action by pre-processing audio signals to identify characteristic trigger patterns before full verification. The first microphone continuously scans for potential triggers using simplified pattern recognition, and only when a match is found does the system activate the second microphone for comprehensive verification. This preliminary filtering reduces the total processing time required while maintaining high accuracy in distinguishing user input from noise.
Data Source
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AI summary
Systems and processes for operating an intelligent automated assistant are provided. In accordance with one example, a method includes, at an electronic device with one or more processors, memory, and a plurality of microphones, sampling, at each of the plurality of microphones of the electronic device, an audio signal to obtain a plurality of audio signals; processing the plurality of audio signals to obtain a plurality of audio streams; and determining, based on the plurality of audio streams, whether any of the plurality of audio signals corresponds to a spoken trigger. The method further includes, in accordance with a determination that the plurality of audio signals corresponds to the spoken trigger, initiating a session of the digital assistant; and in accordance with a determination that the plurality of audio signals does not correspond to the spoken trigger, foregoing initiating a session of the digital assistant.