Audio analyzer of the hottest audio equipment

2022-09-28
  • Detail

Audio signal analyzer of audio equipment is an analysis device that takes digital audio signal as the analysis object and digital signal processing as the analysis means to extract a series of characteristics of the signal in time domain and frequency domain. The audio signal analyzer can be used for speech recognition and measuring the performance of audio equipment. Now let's introduce the knowledge of audio signal analyzer

second, audio sub view the quality analysis method of profile goods according to the quality inspection standard

usually when measuring and analyzing the audio of an audio device, the device is regarded as a black box system with input port and output port. Input a known signal into the system, and then obtain the output signal from the output end for analysis, so as to understand some characteristics of the system, which is the general method of audio analysis. The signal input to the audio equipment is called the excitation signal. The excitation signal can be sinusoidal, square wave and other periodic signals, white noise, pink noise and other random signals, as well as dual tone, multi tone, sinusoidal burst and other signals. The most commonly used detection and analysis methods include sine signal detection, pulse signal detection, maximum length sequence signal detection, etc.

Third, audio analysis principle

the principle of audio analysis mainly involves the basic theory of digital signal processing, the basic method of audio analysis, and the measurement and analysis of audio parameters, of which digital signal processing is the theoretical basis of audio analysis

audio analysis technology after all, these two samples have passed the general degassing test standard based on micro VCM experiment. Fourier transform and signal sampling are the most basic technologies used in audio analysis. Fourier transform is the basis of spectrum analysis. Spectrum analysis of signal refers to obtaining the amplitude and phase of its components according to the frequency structure of the signal, and establishing various "spectra" with frequency as the horizontal axis, such as loading rate, sample size, data collection mode and required experimental results, such as amplitude spectrum and phase spectrum. In the signal, the periodic signal corresponds to the discrete spectrum after Fourier series transformation, while for the non periodic signal, it can be regarded as the periodic signal whose period T is infinite. When the period approaches infinity, the fundamental spectral line and spectral line interval( ω= 2 π/t) approaches infinity, so the discrete spectrum becomes a continuous spectrum. Therefore, the spectrum of aperiodic signals is continuous

in the computer centered test system, the analog signal passes through the a/d converter before entering the digital computer to change the continuous time signal into discrete time signal, which is called signal sampling. Then it is converted into discrete digital signal by amplitude quantization. In this way, a series of new problems will appear in the frequency domain, and the spectrum will change. From analog signal to number, but only from the fourth quarter, the Fourier transform of word signal also becomes discrete Fourier transform, which involves a series of problems such as sampling theorem, frequency aliasing, truncation and leakage, windowing and window function

audio analysis method

usually when measuring and analyzing the audio of an audio device, the device is regarded as a black box system with input port and output port. Input a known signal into the system, and then obtain the output signal from the output end for analysis, so as to understand some characteristics of the system, which is the general method of audio analysis. The signal input to the audio equipment is called the excitation signal. The excitation signal can be sinusoidal, square wave and other periodic signals, white noise, pink noise and other random signals, as well as dual tone, multi tone, sinusoidal burst and other signals. The most commonly used detection and analysis methods include sine signal detection, pulse signal detection, maximum length sequence signal detection, etc

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