Simulations

We have carried out three simulations on segregating two-acoustic sources using noise-added signal f(t), to show that the proposed method can extract the desired signal f₁(t) from it. These simulations are composed as follows:

1.

Extracting an AM complex tone from noise-added AM complex tone.

2.

Extracting one AM complex tone from mixed AM complex tones.

3.

Extracting a speech signal from noisy speech.

We use two types of measures to evaluate the performance of segregation using the proposed method.

One is the power ratio in terms of the amplitude envelope A_k(t), i.e., likely SNR. The aim of using this measure is to evaluate the segregation in terms of the amplitude envelope where signal and noise exist in the same frequency region. This measure is called ``Precision'', and is defined by

$${\rm{Precision}}(k):=10\log_{10}\frac{\int_0^T A_k^2(t)dt}{\int_0^T (A_k(t)-\hat{A}_k(t))^2dt},$$ (29)

where A_k(t) is the amplitude envelope of original signal f₁(t) and $\hat{A}_k(t)$ is the amplitude envelope of the segregated signal $\hat{f}_1(t)$.

The other is the spectrum distortion (SD). The aim of using this measure is to evaluate the extraction of a desired signal $\hat{f}_1(t)$ from noise-added signal f(t). This measure is defined by

$${\rm{SD}}:=\sqrt{\frac{1}{W}\sum_{\omega}^{W}\left(20\log_{10... ...rac{\tilde{F}_1(\omega)}{\tilde{\hat{F}}_1(\omega)}\right)^2},$$ (30)

where $\tilde{F}_1(\omega)$ and $\tilde{\hat{F}}_1(\omega)$ are the amplitude spectrum of f₁(t) and $\hat{f}_1(t)$, respectively. Moreover, frame length is 51.2 ms, frame shift is 25.6 ms, W is analyzable bandwidth of filterbank(about 6 kHz), and the window function is Hamming.

Reduced SD of f₁(t) is the SD difference between f(t) and $\hat{f}_1(t)$.