Selective Acoustic Signal Amplification in Closed Environments
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Solution Overview
Problem
Existing amplification systems in closed environments, such as conference halls and vehicles, fail to selectively amplify the voice of an individual in discomfort amidst multiple acoustic sources, leading to unclear communication and potential missed alerts for urgent needs.
Innovation Solution
An audio engine processes real-time acoustic signals from multiple sensors to identify frequency ranges corresponding to human voices and detect physiological events like pre-defined keywords or frequencies, selecting and amplifying the target signal while canceling other acoustic signals using active noise cancellation techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all acoustic signals are amplified in a closed environment with multiple speakers, then all voices are made audible, but it results in chaos and makes it difficult to hear any particular individual
Solution Approach 1:
The system segments the mixed acoustic signals by analyzing frequency ranges to identify and separate individual voices from the overall acoustic environment, allowing selective amplification of specific speakers rather than amplifying all sounds equally
Solution Approach 2:
The system applies different processing qualities to different acoustic signals based on their characteristics, selectively amplifying certain frequency ranges corresponding to specific speakers while applying noise cancellation to others, creating localized audio enhancement rather than uniform processing
2Measurement precision
If microphones capture all voices in a closed environment, then all acoustic signals are recorded, but the system cannot detect only the voice of an individual in discomfort
Solution Approach 1:
The system changes the parameter of frequency range analysis to identify specific voice characteristics, comparing captured acoustic signals against known frequency ranges of human speech to detect and isolate voices of individuals in discomfort from the general acoustic environment
3Reliability
If the amplification system amplifies all acoustic signals, then no voice is lost, but urgent signals from individuals in discomfort get unnoticed among other voices
Solution Approach 1:
The system performs preliminary analysis of acoustic signals by comparing frequency ranges to identify potential urgent signals before full amplification, allowing early detection and prioritization of voices that may indicate discomfort or require attention
Solution Approach 2:
The system extracts and isolates specific acoustic signals that match the characteristics of urgent or distressed voices, separating them from the general acoustic background for focused amplification and attention
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution ensures clear amplification of the target signal, providing immediate attention to individuals in discomfort by effectively canceling unwanted noise and enhancing communication in crowded spaces.
Implementation Method 1
The audio engine may process the plurality of acoustic signals to obtain the frequency ranges for each of the plurality of acoustic signals. The audio engine may compare frequency ranges pertaining to each of the plurality of acoustic signals with frequency ranges of human voices
Implementation Method 2
the amplification engine may select an acoustic signal as a target signal, wherein the target signal is indicative of the acoustic signal triggering the physiological event. Thereafter, the amplification engine may amplify the target signal within the closed environment
Implementation Method 3
the amplification engine may generate an interfering signal to cancel other acoustic signals within the closed environment
Data Source
AI summary
The present subject matter relates to systems and methods for selectively amplifying an acoustic signal in a closed environment. In an implementation, a plurality of acoustic signals may be received from within the closed environment. Frequency ranges corresponding to each acoustic signal may be obtained and compared to determine presence of at least one individual in the closed environment. Acoustic signals pertaining to the at least one individual may be analysed to detect occurrence of a physiological event. Based on the analysis, the acoustic signal may be recognized as a target signal, and the target signal may be amplified in the closed environment. Further, an interfering signal may be generated to cancel other acoustic signals within the closed environment.