Headphone Alert System for Preference-Based External Sound Detection
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Solution Overview
Problem
Current headphones are 'blind systems' that fail to alert users of important external sounds, such as announcements or emergency calls, while listening to audio, as they cannot differentiate between ambient noise and media playback, and user preferences vary by environment and social context.
Innovation Solution
A system that includes a computer-program product and apparatus to receive ambient noise, extract speech components, derive intent, and compare it to user-defined preferences, transmitting alerts via headphones or mobile devices when a match is found, using a server and machine learning to adapt preferences based on context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If headphones play audio at high volume, then media playback quality is improved, but user ability to hear external sounds deteriorates
Solution Approach 1:
The patent segments the audio output into two separate channels: one for media playback through headphones and another for external sound alerts through the same headphones. The system processes ambient noise separately, extracts speech components, and delivers them as distinct alert signals, allowing simultaneous media enjoyment and external awareness without mixing the two audio streams.
Solution Approach 2:
The patent introduces an intermediary system consisting of external microphones, signal processing unit, and alert generation mechanism. This intermediary captures external sounds, processes them to extract meaningful speech components, and translates them into alert signals that can be heard through headphones without interfering with media playback, thus mediating between the conflicting needs of high-volume media and external awareness.
2Loss of energy
If headphones block all ambient noise, then media immersion is improved, but user awareness of important external sounds deteriorates
Solution Approach 1:
The system employs self-service through automatic speech detection and classification algorithms that continuously monitor ambient noise, identify speech components, determine their importance based on predefined criteria, and generate alerts autonomously without requiring user intervention. This maintains media immersion while reliably detecting important external sounds.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors external sounds, processes them through speech recognition, and provides real-time alert feedback to the user through the headphones. This closed-loop feedback ensures that important external sounds are reliably detected and communicated while maintaining the primary media experience.
3Difficulty of detecting and measuring
If system monitors all ambient noise, then external sound detection capability is improved, but processing complexity increases
Solution Approach 1:
The patent extracts only the relevant speech components from the full ambient noise spectrum using speech detection algorithms. Instead of processing all ambient sounds equally, the system identifies and extracts speech-like signals, filters out irrelevant noises, and focuses processing resources only on potential alert-worthy speech components, thereby reducing overall processing complexity.
Solution Approach 2:
The system applies different processing qualities to different portions of the ambient noise spectrum. Speech components receive intensive processing with speech recognition and intent analysis, while non-speech ambient noises receive minimal or no processing. This localized quality approach optimizes detection capability for important sounds while minimizing unnecessary processing complexity.
4Loss of information
If system provides all external sound alerts, then user awareness is improved, but user preference customization is reduced
Solution Approach 1:
The patent implements dynamic user preference configuration where alert criteria, speech keywords, importance thresholds, and notification methods can be adjusted in real-time based on user context, environment, and personal preferences. The system adapts its monitoring and alerting behavior dynamically rather than providing fixed uniform alerts, allowing users to customize which external sounds trigger alerts and how they are delivered.
Data Source
AI summary
A computer-program product embodied in a non-transitory computer readable medium that is programmed to communicate with a listener of headphones is provided. The computer-program product includes instructions to receive ambient noise indicative of external noise to a listener's headphone and to extract a speech component from the ambient noise. The computer-program product further includes instructions to derive an intent from the speech component of the ambient noise and compare the intent to at least one user defined preference. The computer-program product further including instructions to transmit an alert to notify a listener that the intent of the speech component matches the at least one user defined preference.