Audio Cue Detection Module for Low-Power Contextual Computing
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Solution Overview
Problem
Mobile devices face limitations in processing and sensory capabilities due to constraints on resources such as battery power, wireless network capacity, and CPU processing speed, which hinder the realization of advanced functionalities like contextual computing.
Innovation Solution
A method involving the use of a cue detection module that processes audio input to discern characteristics, allowing for the control of processor operations and enabling or disabling policies on electronic devices based on derived data, thereby optimizing resource usage and enhancing contextual computing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If audio processing is performed continuously to enable contextual computing, then contextual awareness is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the level of audio processing based on detected cues. When cues indicating contextual relevance are detected, full processing is activated. When no such cues are present, processing is reduced or suspended, allowing the system to adapt its computational effort to actual needs rather than operating at constant high intensity
Solution Approach 2:
The audio processing system monitors its own operational context and automatically regulates its own power consumption. By detecting cues in the audio stream itself, the system determines when processing is necessary and when it can be minimized, making the power management self-regulating without requiring external intervention
2Power
If multiple processors are used to enhance processing capabilities, then computational power is improved, but device complexity increases
Solution Approach 1:
The processing system is divided into distinct functional components, each handling specific aspects of audio analysis. This segmentation allows the system to distribute computational tasks across multiple processors or processor cores, with each component specialized for particular processing functions, thereby managing complexity through functional decomposition
Solution Approach 2:
The multiple processors are designed to perform multiple functions - handling not only audio processing but also other computational tasks. This multi-functionality reduces the need for dedicated specialized hardware for each function, thereby managing device complexity while maintaining high computational power through resource sharing
3Measurement precision
If audio processing is optimized for accuracy, then detection precision is improved, but processing time increases
Solution Approach 1:
The system performs partial processing initially to obtain quick results, then applies more intensive analysis only when needed. Rather than always performing complete accurate analysis, the system uses a two-stage approach: quick preliminary detection followed by detailed analysis only for promising candidates, thereby reducing average processing time while maintaining accuracy when required
Data Source
AI summary
Methods and arrangements involving electronic devices, such as smartphones, tablet computers, wearable devices, etc., are disclosed. One arrangement involves a low-power processing technique for discerning cues from audio input. Another involves a technique for detecting audio activity based on the Kullback-Liebler divergence (KLD) (or a modified version thereof) of the audio input. Still other arrangements concern techniques for managing the manner in which policies are embodied on an electronic device. Others relate to distributed computing techniques. A great variety of other features are also detailed.