mmse-lsa speech enhancement method based on improved noise estimation
A MMSE-LSA, speech enhancement technology, applied in speech analysis, instruments, etc., can solve problems such as noise residue, achieve the effects of reducing speech distortion, suppressing noise, and reducing errors
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Embodiment 1
[0071] like figure 1 As shown, the present embodiment relates to a MMSE-LSA speech enhancement method based on improved noise estimation, comprising the following steps:
[0072] S1: Framing and windowing the noisy speech, and then doing short-time Fourier transform to obtain the amplitude spectrum and phase angle of the noisy speech;
[0073] S2: Calculate the logarithmic energy and spectral entropy of the noisy speech according to the result of step S1, and construct a new speech characteristic parameter energy-entropy ratio;
[0074] S3: According to the properties of the energy entropy ratio and the voice existence probability in step S2, the energy entropy ratio and the voice existence probability are proportional to each other, and the mathematical relationship model between the energy entropy ratio and the voice existence probability is established to obtain the estimated value of the voice existence probability;
[0075] S4: Smooth the estimated value of the speech ex...
Embodiment 2
[0085] like figure 1 As shown, the present embodiment is based on Embodiment 1. In the step S2, the logarithmic energy is usually significantly larger than the non-speech segment according to the short-term energy of the speech segment, specifically as follows,
[0086] If it is assumed that the noisy speech signal of the i-th frame after frame division and windowing is , then the short-term energy of the frame is:
[0087]
[0088] Among them, N is the frame length, further improving the energy calculation to obtain the logarithmic energy:
[0089]
[0090] In the formula, α takes 2.1.
Embodiment 3
[0092] like figure 1 As shown, on the basis of Embodiment 1 or 2 in this embodiment, in the step S2, the spectral entropy can be obtained by the following formula,
[0093] Let the speech signal of the i-th frame after windowing and framing of the noisy speech signal be , after Fourier transform, let the power spectrum of the kth frequency component be , then the normalized probability density function of each frequency component is:
[0094]
[0095] Then the spectral entropy of each analysis frame is:
[0096] .
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