Dynamic Buffer Adjustment for Wireless Audio Power Reduction
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Solution Overview
Problem
Mobile devices, when wirelessly coupled, experience increased power consumption, which reduces their battery life, and existing solutions do not effectively address this issue to extend battery life while maintaining functionality.
Innovation Solution
A system where a primary device and a secondary device, such as a smartphone and a smartwatch, use low power wake on voice components and deep sleep modes to dynamically adjust buffer sizes and processing based on audio data energy levels and key phrase detection, reducing power consumption by optimizing data transmission and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile devices are wirelessly coupled to enable access to functionalities of both devices, then device functionality and accessibility are improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the buffer size based on the energy level of audio data. When audio energy is high (indicating active speech), the buffer size is reduced to minimize data transmission. When audio energy is low (indicating silence or background noise), the buffer size is increased to accumulate more data before transmission. This dynamic adjustment optimizes power consumption while maintaining voice interaction functionality.
Solution Approach 2:
The patent changes the buffer size parameter based on detected audio energy levels and key phrase detection results. By modifying this operational parameter in response to environmental conditions, the system achieves lower power consumption during wireless coupling while preserving the ability to access functionalities of both devices.
2Measurement precision
If buffer sizes are increased to capture more audio data, then audio capture quality is improved, but power consumption increases due to more data transmission
Solution Approach 1:
The buffer size is not fixed but dynamically adjusted based on real-time analysis of audio energy levels. This allows the system to capture sufficient audio data for quality voice recognition while minimizing the amount of data that needs to be transmitted to the paired device, thereby reducing power consumption.
Solution Approach 2:
The system continuously monitors audio energy levels and uses this feedback to adjust buffer size. When high energy levels are detected (indicating active speech), the buffer size is reduced. When low energy levels are detected (indicating silence), the buffer size is increased. This feedback mechanism optimizes the balance between audio capture quality and power consumption.
3Speed
If devices remain in active mode to maintain responsiveness, then response time is improved, but power consumption increases
Solution Approach 1:
Instead of remaining continuously active, the system uses periodic key phrase detection and audio energy analysis to determine when full processing is needed. The wearable device can operate in a lower power state between these periodic checks, only transitioning to full active mode when a key phrase is detected or audio energy exceeds a threshold, thus balancing response time with power consumption.
Data Source
AI summary
Apparatus and method to facilitate power consumption reduction in one or both of a first and second device are disclosed herein. In some embodiments, the first device may include one or more antennas that is to receive first audio data captured by the second device; and one or more processors in communication with the one or more antennas. The one or more processors is to identify a first energy level associated with the first audio data, determine, in accordance with the first energy level, a size of a buffer to be updated in the second device to capture second audio data, and detect whether one or more key phrases is included in the first audio data, which may be repeated depending on the no, one, or more key phrases detected.