| Citation: | ZHOU K，CHEN W J，CHEN W H，et al. Extended subtraction speech enhancement based on cubic spline interpolation[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（10）：2826-2834 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0744
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The speech recognition system is susceptible to noise. In order to filter noise, traditional speech enhancement methods such as spectral subtraction are often used by researchers, but these methods are troubled by “music noise”. To solve this problem, a speech enhancement algorithm based on cubic spline interpolation is proposed in this paper. Firstly, speech is subjected to the fractional Fourier transform, spectral subtraction is employed to preprocess noisy speech, and the Wiener filter noise estimator is utilized to realize the iterative update of noise. Secondly, the speech with noise and the estimated noise is functioned by cubic spline interpolation. A geometric spectrum subtraction algorithm is then used to process the functional speech with noise and the estimated noise to produce the pure speech. The simulation results show that compared with the traditional speech noise reduction algorithm, the proposed algorithm has an obvious effect on improving the “music noise” problem, and also greatly improves speech intelligibility and speech quality.
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