AI noise reduction technology is based on deep neural networks (DNNs). Through a large number of noise and clear speech samples, it is trained to enable the neural network to learn the characteristic patterns of different noises and clear speech. Its core algorithms include convolutional neural networks (CNNs), recurrent neural networks (RNNs) and some variants (such as LSTM and GRU), and generative adversarial networks (GANs). These algorithms can effectively process audio signals in complex noise environments, dynamically adjust noise reduction strategies, and retain the naturalness and clarity of speech.
Application scenarios:
AI noise reduction technology can effectively suppress background noise, such as keyboard sounds, fan sounds, etc., and significantly improve voice clarity.
BP620, a digital handheld radio, is equipped with a high-performance speaker + AI intelligent noise reduction algorithm, which can effectively filter background noise, eliminate howling, and accurately extract human voices, ensuring that radio sounds can still be accurately captured in various noisy areas, achieving clear and loud call effects.
Voice assistants and smart devices: In noisy environments, AI noise reduction technology can improve the accuracy of voice recognition and ensure that the device can accurately understand user commands
Music recording and live broadcast: AI noise reduction technology can be used to remove environmental noise and improve recording quality, especially for non-professional recording environments
In-vehicle communications: AI noise reduction technology can eliminate background noise such as road noise and wind noise in the car, and improve the experience of voice calls and voice assistants
Advantages:
Highly adaptable: can automatically adapt to different noise environments and dynamically adjust noise reduction strategies
Strong complex noise processing capabilities: can effectively handle various types of noise, including non-steady-state noise
Good sound quality retention: while reducing noise, it can retain the naturalness and clarity of the voice
