4 results about "Noise assessment" patented technology

The invention discloses a noise robustness auditory decoding method and system based on an adversarial domain adaptation network, and relates to the technical field of auditory decoding, and the method comprises the steps: obtaining a multi-channel electroencephalogram signal, and carrying out the parallel analysis and feature fusion; inputting the multi-dimensional signal integrity feature vector into a noise evaluation model, and outputting a noise complexity score; calling a feature decoupling module, and outputting a task-related feature vector and a noise-related feature vector; inputting the task related feature vectors into an attention decoder to obtain auditory attention distribution probability distribution; and an auditory attention distribution probability distribution and noise traceability and influence report is used as a noise robustness auditory decoding result of the target user. The technical problems that an existing auditory decoding method is low in decoding precision and insufficient in robustness in a noisy scene are solved.

This invention relates to the field of noise environmental impact assessment technology, and discloses a method and related apparatus for assessing the noise environmental impact of onshore wind farms. The method first constructs a discretized representation containing spatial coordinates, calculates noise propagation attenuation and directional parameters, and establishes a propagation path feature association array; it then matches the wind turbine sound power level with hourly meteorological data of the assessment benchmark year, determines the directivity correction amount, and forms a complete propagation array containing time-varying sound source parameters; it calculates and superimposes the hourly noise contribution value of each wind turbine, obtains the daily continuous equivalent sound level through energy averaging, and extracts the maximum continuous equivalent sound level as an evaluation index; based on the index, it generates a spatial distribution report of noise impact. This invention constructs a dynamic sound source intensity model, uses a gridded array algorithm to improve computational efficiency, comprehensively considers multiple attenuation mechanisms and the superposition effect of multiple wind turbines, accurately reflects the actual operating conditions of the wind farm, and significantly improves the accuracy and scientific nature of the noise assessment results.

The invention discloses an intelligent hearing aid noise reduction method combined with environmental noise evaluation, and relates to the technical field of hearing aid signal processing, comprising the following steps: collecting an audio signal and converting the audio signal to a frequency domain to obtain a frequency domain signal; extracting noise features from the frequency domain signal, calculating a noise time-varying index and spectrum flatness, and identifying an environmental noise type; estimating a noise power spectrum, determining a noise tracking parameter according to the environment noise type, and updating the noise power spectrum; calculating a signal-to-noise ratio parameter corresponding to the noise power spectrum, determining a noise reduction intensity factor according to the environmental noise type and the hearing characteristics of the user, and calculating a noise reduction gain based on the signal-to-noise ratio parameter and the noise reduction intensity factor; and performing noise reduction processing on the frequency domain signal by using the noise reduction gain, and converting the frequency domain signal to a time domain to output a processed audio signal. According to the invention, the noise tracking parameter is adaptively adjusted by identifying the environmental noise type, and the noise reduction intensity is determined in combination with the hearing characteristics of the user, so that the noise reduction effect and the user suitability of the hearing aid in a complex environment are improved.

The application discloses a noise robustness hearing decoding method and system based on an adversarial domain adaptation network, relates to the technical field of hearing decoding, and comprises the following steps: acquiring a multi-channel electroencephalogram signal, and performing parallel analysis and feature fusion; inputting a multi-dimensional signal integrity feature vector into a noise evaluation model to output a noise complexity score; calling a feature decoupling module to output a task-related feature vector and a noise-related feature vector; inputting the task-related feature vector into an attention decoder to obtain a hearing attention allocation probability distribution; and taking the hearing attention allocation probability distribution and a noise tracing and influence report as a noise robustness hearing decoding result of a target user. The technical problem of low decoding accuracy and insufficient robustness of existing hearing decoding methods in a noisy scene is solved.