AI-NR (artificial intelligence noise reduction)

Definition:

Noise reduction technology based on deep learning, by training neural network model to identify noise features (such as keyboard sound, street noise), to achieve more accurate noise separation and suppression.

Core advantages:

Adaptive scenarios: You can learn noise patterns in different environments (such as offices, airports, and exhibitions) through large amounts of data, and dynamically adjust noise reduction strategies.

Retain details: Compared with traditional noise reduction algorithms (which may accidentally delete high-frequency vocal details),AI-NR can more intelligently distinguish the spectral overlap between noise and human voice (such as human voice in cough).

Application Scenarios:

Open headphones: When walking or riding, real-time traffic noise is reduced, while environmental warning sounds (such as car whistles and pedestrian reminders) are retained to ensure safety.

Telemedicine devices: separating background monitor noise from the patient's cardiopulmonary sounds to assist doctors in more accurate auscultation.

Technical value:

Break through the "one size fits all" limitation of traditional noise reduction, and realize "intelligent perception dynamic noise reduction", especially suitable for complex and changeable noise environment (such as mixed noise and unsteady noise).