Signal Processing TRIZ Cases

A hearing device uses a proximity sensor to detect nearby objects and adjust feedback cancellation parameters.

A hearing device presents acoustic signals from virtual positions, allowing users to select settings by moving their body part toward the sound source.

An active audio device uses an AI determination unit to analyze external signals and automatically adjust output settings.

Coincident vertically-stacked directional microphones determine azimuth and elevation angles from stereo audio signals.

A communications management system transmits unique signals to participant devices to identify audio sources.

Segmented volume controls allow patients to adjust electrical and acoustic stimulation levels independently, resolving fixed balance limitations.

Ear-worn device uses voice signatures to isolate target speaker audio via machine learning processing.

Device detects prominent sounds to switch between silent and ringing modes, reducing meeting disturbances.

A display device adjusts hearing aid volume through a Bluetooth connection using ambient sound data.

A blind source separation method combines independent component analysis with non-negative matrix factorization to process mixed audio signals.

Electronic device adjusts call audio output intensity based on user proximity detection to prevent privacy leakage from unintended external exposure.

An echo canceller uses a digital reference signal derived from the analog audio input to isolate user voice commands from mixed acoustic signals.

Synthesize distinct acoustic parameters per loudspeaker channel to resolve directional accuracy trade-offs in virtual reality reverberation.

A hearing device volume control curve segments amplification into soft and loud ranges for continuous dynamic adjustment.

Digital beamforming in open-sphere arrays creates directional sensitivity without bulky hardware, maintaining high-frequency performance.

Bandpass filtering isolates relevant frequency components to measure transducer impedance, compensating for variable ear channel geometries.

Neural networks calculate spectral masks to transform low-cost microphone inputs into high-fidelity audio signals.

Segmented sub-apertures in the acoustic receiver array resolve localization accuracy and detection range trade-offs for large-area monitoring.

A sensor apparatus integrates inertial and structure-borne sound sensors with dynamic frequency control to prevent signal interference.

A multi-stream rendering system processes simultaneous audio program streams over arbitrarily placed loudspeakers.

A power-smoothing circuit filters frequency-varying input signals to reduce energy usage in active medical devices.

A microphone array synchronizes sound data using time differences to generate an amplified source signal for precise location determination.

Segmentation and intermediary processing reduce system complexity while maintaining high emotion recognition accuracy.

Central processing unit subtracts presentation audio from sensor input to isolate differential signals, preventing false alarms from movie or stage soundtracks.

Self-mixing interferometry sensors detect user gestures on earbuds using coherent light interference patterns to distinguish inputs from environmental noise.

An adaptive masking filter suppresses specific audio frequencies to eliminate howling noise in vehicle communication systems.

Auxiliary signal path reduces frequency bandwidth to calculate reduction parameters for main path noise suppression.

Audio control system adjusts microphone signal magnitudes at specific frequencies based on detected road type and smoothness.