Buffered Audio Assistant Architecture for Low-Latency Response
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Solution Overview
Problem
Existing digital assistants incur latencies between user request and response, wasting user time and device energy, particularly in battery-operated devices.
Innovation Solution
Implementing a digital assistant with two processors, where a first processor captures and analyzes audio input, and a second processor identifies tasks only when predetermined criteria are met, reducing unnecessary task identification and conserving power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the digital assistant continuously monitors audio input and immediately processes user requests, then the response speed is improved, but the energy consumption increases
Solution Approach 1:
The system performs preliminary actions by continuously capturing and buffering audio input in the background before an actual user request is made. This allows the audio data to be ready for immediate processing when a user speaks, achieving fast response times without continuously activating the full processing pipeline and thus conserving energy.
Solution Approach 2:
The digital assistant system is segmented into two distinct processor components: a first processor that handles continuous audio capture and buffering, and a second processor that handles task identification and processing. This segmentation allows the energy-intensive processing to occur only when needed, while the low-power audio capture runs continuously, resolving the contradiction between fast response and energy conservation.
2Measurement precision
If the digital assistant processes all audio input through task identification, then the accuracy of task recognition is improved, but the processing time and energy waste increase
Solution Approach 1:
The system applies partial action by having the first processor perform only audio capture and buffering, while the second processor performs task identification only when criteria are met. This partial division ensures that full processing accuracy is achieved when needed, while avoiding unnecessary processing time and energy consumption for continuous audio streams.
3Device complexity
If the digital assistant uses a single processor for all functions, then the device complexity is reduced, but the latency between user request and response increases
Solution Approach 1:
The system is segmented into two specialized processors: a first processor dedicated to audio capture and buffering, and a second processor dedicated to task identification. This segmentation eliminates the latency that would occur in a single-processor system by having each processor专注于 its specific function, allowing parallel operation and faster overall response time.
Data Source
AI summary
An electronic device can implement a zero-latency digital assistant by capturing audio input from a microphone and using a first processor to write audio data representing the captured audio input to a memory buffer. In response to detecting a user input while capturing the audio input, the device can determine whether the user input meets a predetermined criteria. If the user input meets the criteria, the device can use a second processor to identify and execute a task based on at least a portion of the contents of the memory buffer.