基于对数处理机制和时频掩蔽估计的语音增强

doi:10.16180/j.cnki.issn1007-7820.2025.01.007

Abstract

Abstract:

In view of the problem of inaccurate speech estimation by time-spectrum model, this study proposes a model transformation method to obtain the logarithmic probability density function of noise and speech. With the help of the logarithmic relationship among noisy speech, clean speech and noise, and the MMSE(Minimum Mean Square Error) estimation theory, a time-frequency mask of the estimating log-spectrum of speech is derived. A soft mask is also derived based on the logarithmic probability distribution of speech and noise, which can weight the logarithmic subbands of noisy speech to reduce noise and improve the accuracy of speech estimation. The simulation results show that compared with unprocessed noisy speech, the proposed method has an improvement of more than 3 dB in noise suppression. The average improvement in auditory perception of time-frequency mask and soft mask based on MMSE is 27.7% and 29.4%, and the average improvement in intelligibility is 12.7% and 14.3%, respectively.

Key words: speech processing, speech enhancement, logarithmic probability density function, time-frequency mask, noise suppression, unsupervised learning, soft mask, logarithmic spectrum

CLC Number:

TN912.35

WANG Xianyun, DOU Shanshan, CHENG Chuhao. Speech Enhancement Based on the Logarithmic Processing and Time Frequency Masking Estimation[J].Electronic Science and Technology, 2025, 38(1): 45-51.

Figures/Tables 3

Figure 1.

Table 1.

Table 2.

References 23

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噪声类型	信噪比/dB	不同方法
噪声类型	信噪比/dB	含噪	Ref.1	Ref.2	Ref.3	Ref.4	MASK_MMSE	MASK_P
White	-5	1.330	1.660	1.756	1.782	1.767	1.819	1.956
	0	1.564	2.058	2.185	2.217	2.189	2.265	2.384
	5	1.875	2.450	2.581	2.614	2.607	2.657	2.742
	10	2.249	2.813	2.937	2.965	2.968	2.993	3.064
Babble	-5	1.398	1.635	1.656	1.698	1.649	1.656	1.652
	0	1.791	2.025	2.060	2.082	2.049	2.070	2.069
	5	2.157	2.390	2.431	2.441	2.435	2.439	2.435
	10	2.502	2.724	2.764	2.771	2.766	2.772	2.768
F16	-5	1.379	1.823	1.918	1.940	1.911	1.962	2.021
	0	1.717	2.217	2.313	2.336	2.309	2.366	2.430
	5	2.092	2.577	2.681	2.707	2.684	2.738	2.801
	10	2.444	2.923	3.037	3.067	3.044	3.095	3.154
Factory	-5	1.345	1.718	1.787	1.780	1.775	1.808	1.820
	0	1.707	2.106	2.188	2.208	2.186	2.226	2.235
	5	2.092	2.501	2.584	2.604	2.602	2.615	2.614
	10	2.477	2.864	2.944	2.962	2.960	2.964	2.963
均值	-	1.882	2.281	2.364	2.385	2.368	2.403	2.435

噪声类型	信噪比/dB	不同方法
噪声类型	信噪比/dB	含噪/%	Ref.1/%	Ref.2/%	Ref.3/%	Ref.4/%	MASK_MMSE/%	MASK_P/%
White	-5	31.15	37.56	37.91	37.97	37.90	37.48	38.16
	0	43.77	50.42	51.00	51.11	50.95	50.91	52.04
	5	56.17	62.60	63.24	63.36	63.24	63.36	64.33
	10	68.01	73.78	74.32	74.41	74.42	74.43	74.69
Babble	-5	31.53	34.52	34.80	34.83	34.79	34.41	34.54
	0	45.78	49.66	50.22	50.33	50.20	50.04	50.39
	5	59.58	63.47	64.21	64.38	64.08	64.34	64.93
	10	71.34	74.57	75.19	75.35	75.17	75.30	75.80
F16	-5	30.60	37.63	38.39	38.51	38.18	37.98	39.37
	0	44.13	52.15	53.30	53.55	53.10	53.37	55.30
	5	57.77	65.78	67.09	67.41	66.91	67.60	69.47
	10	70.17	77.107	78.21	78.48	78.18	78.62	79.77
Factory	-5	32.29	38.36	38.90	38.91	38.74	38.45	38.92
	0	46.53	53.21	54.05	54.21	53.92	53.93	54.65
	5	60.49	66.59	67.58	67.80	67.34	67.80	68.56
	10	72.49	77.19	78.01	78.21	77.88	78.30	78.80
均值	-	51.36	57.16	57.89	58.05	57.81	57.89	58.72

Speech Enhancement Based on the Logarithmic Processing and Time Frequency Masking Estimation

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