Noise suppression has become an essential requirement for numerous acoustic devices, mobile phones and surveillance equipment. One standard criterion for almost digital signal processing is the saving of the target speech component while eliminating all background noise and interferences. Dual - microphone system is one of the most basic elements, which is widely commonly installed in speech applications. However, the designed signal processing faces many complex challenges in extracting the directional sound source. In this paper, the author proposed using an additive post-filtering to improve the author's previous research's performance. The evaluated experiment has confirmed the desired noise reduction to 5.5 (dB) and increasing the speech quality in terms of the signal-to-noise ratio from 3.2 (dB) to 5.7 (dB).
The demand of noise suppression in almost speech processing applications like speech recognition, hearing aids, cell phone, surveillance equipment, smart home applications to work anytime and anywhere, makes them has the capacity of reducing the effect of annoying disturbances, like background noise, interferences, third - party or surrounding vehicle transport. To decrease the degradation of desired target talker in terms of speech quality, speech intelligibility, the single and multi - microphone noise reduction approach are often applied for signal processing. Spectral estimation technique is the most widely implemented in single - channel techniques, such as: subspace method, Wiener filter and spectral subtraction, are based on calculation of the noise power with assumption that the background noise are stationary, or under the situation with ambient speech noise.
The microphone array beamforming [
Dual - microphone system (DMA2) has numerous advantages for signal processing. DMA2 owns compact, easy to implement MA digital signal processing. In the previous work [23], the author suggested an effective method for separating each target, which stands at two opposite directions. However, in the real-life world, due to its undetermined recording situations, the performance also corrupted. In this contribution, the author proposed using an additive post - filtering to block the remaining noisy component after using [23]. The numerical results have rated the better performance of noise suppression to 5.5 (dB) and increasing of the speech quality from 3.2 to 5.7 (dB). The purpose of this article is demonstrating a new effective technique to enhance speech enhancement, which based on DMA2.
The remaining section of this article is organized as follows. The next section describes the signal model of DMA2 and the author’s previous evaluation. Section III demonstrated additive post - Filtering, which uses MMSE estimator. Section IV shows the illustrated experiment and Section V concludes the purpose of this paper.
A scheme of principal working of a certain differential microphone array (DMA2) [24 - 30] is illustrated in Figure 4. DMA2 owns high directional beampattern, high noise reduction and easy implemented to form a beampattern toward the sound source. DMA2 has a compact size, and is very suitable for microphone array technique, digital signal processing method to block surrounding noise environment and save the target desired speaker.
With the definition , is the frequency index and current considered frame. We denote the speech propagation of sound source is (343 / ), is distance between two installed microphones, 0 = / is the sound delay, the direction of arrival of useful signal is , = 0 ( ). The representation of two captured microphone array signals in the frequency-domain defined can be expressed as the following way: 1( , ) = ( , ) 2( , ) = ( , ) − (1) (2)
With a defined time, delay is added, the directivity pattern of the processed signal is obtained by determined value of . DMA2 is used for extracting two directional different speakers at opposite directions. The output of DMA, which exploits subtraction signal between 1( , ), 2( , ) can be illustrated that:
The value of ( )is limited with a determined threshold 12(dB). This equalizer ensures deriving desired signal.
So finally, the received signals are: 1( , )= 1 2( , )= 2 ( , )× ( ) ( , )× ( ) (10) (11) (12) (13) (14)
estimator [21] is used for estimation a spectral gain:
The central ideal of suggested post - Filtering is based on the estimation of noise power. The MMSE 1( , )= √ ( , ) ( , ) [Г(1 + 2
) (− 2;1;− ( , ))] 1 ( , )+1 Where ( , )≜ ( , )
( , ) ; ( ; ; )is the confluent hypergeometric function. The author proposed the calculation of a priori SNR ( , ) and a posteriori SNR ( , ) as the following equations: ( , )=
[| 1( , )|2] [| 2
( , )|2] ( , )= [|[|2 1( , )|2]
( , )|2]
With a defined appropriate value , the obtained gain function by MMSE estimator can be used as an effective post - Filtering. In single - channel approach, the 1 ( , )is applied to gain the desired speech component while suppressing noise level. In the next section, this post - Filtering has the ability of preserving the target speaker while decreasing the background noise and enhancing the overall performance.
In this section, the author illustrated an experiment to enhance the performance of DMA2 in noise reduction. This experiment is conducted in a living room, where in presence of annoying background noise, diffuse noise field. The speaker in stand at = 2( ) to the DMA2. For further to rate the performance, an objective measurement [22] is used for calculating the speech quality of the previous work and additive post - Filtering. Two microphone array signals are sampled at = 16 , and transformed in the frequency domain with these parameters: = 512, overlap 50%.
The waveform of the original microphone array signal can be expressed in Figure 7. From 0 - 1.4 (s), the speech component of desired talker exits, and from 1.6 - 3 (s), there are only direction noise source.
Using [23], the obtained waveform is shown in Figure 8.
By using the post - Filtering, the effectiveness of noise reduction can be obtained. The processed signal is shown in Figure 9.
The overall energy of microphone array signal, the processed signals by [23], and post – Filtering is depicted in Figure 10.
As we can see that, the advantage of post - Filtering is presented. The achieved noise reduction is to 5.5 (dB), and the speech quality in the terms of the signal - to - noise ratio (SNR) is increased from 3.2 (dB) to 5.7 (dB).
An essential problem is almost signal processing is achievement of more robust noise reduction. DMA2 is one of the most widely common installed in numerous speech applications, such as mobile phone, surveillance equipment, smart home, teleconferencing due to its compact. Therefore, an effective post - Filtering for DMA2 is an attractive research direction. In this section, the improvement of noise reduction has been confirmed. The numerical results show that proposed post - Filtering allows obtaining better performance in DMA2.
DMA2 has the capacity of compact arrangements, low size and promise high directional beampattern, high gain the output signal in comparison with other MA beamforming. However, DMA owns its drawback that even the complex noisy environment can corrupt its performance. For many several speech applications, decreasing speech distortion or noise suppression is always a considered problem. In this research, the author has presented and demonstrated a post - Filtering for enhancing the DMA2’s performance in realistic recording scenario. The author has shown how the noisy component at certain direction can be suppressed, and the speech quality of DMA2’s evaluation was increased in comparison with the author’s previous work. This post - Filtering can be integrated into multi-microphone system, which use other different MA beamforming.
This research was supported by Digital Agriculture Cooperative. The author thanks our colleagues from Digital Agriculture Cooperative, who provided insight and expertise that greatly assisted the research.
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