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Speckles noise generated by the relative in-plane motion between the Laser Doppler Vibrometry (LDV) and the target damages the quality of the LDV-captured speech severely. As such, it is necessary to research on the effect of speckles noise on the LDV for remote voice detection and remove it. In this paper, we comprehensively discuss the statistical properties of dynamic speckles with the combination of theories and experiments, and the results show that the fluctuation of speckles intensity depends strongly on the relative velocity for a given value of the detection distance. Then, we investigate the effects of the speckles noise on the LDV for remote audio detection, and the results indicate that speckles noise can cause spikes and bursts appearing in the LDV-captured voice signals, which degrades the quality of the speech. To address this issue, an algorithm of the speckle noise reduction in the LDV-measured audio signals is proposed and the experimental results demonstrate that the proposed algorithm performs well.

To address the challenges of non-cooperative and remote human activity detection, a multimodal remote audio/video acquisition system is developed. The system mainly consists of a Pan-Tilt-Zoom (PTZ) camera and a Laser Doppler Virbometer (LDV). The traditional all-fiber structure has residual carriers, which degrades the system performance badly. To solve the problem, a partial-fiber LDV is developed to obtain remote audio by detecting the vibration of the object (caused by the acoustic pressure around the target). Besides, to improve the quality of LDV audio signals, a speech enhancement algorithm (OM-LSA) is applied to remove noises in the LDV audio signals. The PTZ camera can provide remote visual information. We also use the YOLO algorithm to discriminate human from the photos which are updated from the PTZ camera continuously. That is the primary application of the YOLO algorithm. Moreover, the YOLO algorithm is used to recognize the objects around the target person by processing the video signals acquired by PTZ camera, which can aid the LDV in finding a suitable vibration target. In experiments, we show that the remote (50 m) speech signals and visual signals can be obtained by this surveillance system. That means this system has the ability to detect remote human activities.

Speaker recognition technique is one of the popular biometric identification technology, which identifies the speaker’s identity based on the speaker’s voice. Whereas almost all speaker verification system shows poor performance when the system and speaker are far apart. To address the challenges of remote speaker recognition, a Laser Doppler Vibrometer (LDV) is used to recognize remote speaker. In this paper, three LDV speech corpuses, each consists of 50 speakers, are collected from the vibrations of a plastic bag, a mineral water bottle and a computer screen, using the LDV developed by us. The distance from the LDV sensor to the vibration targets is approximately 50 m. In order to improve the quality of the LDV-captured speech, the speech enhancement technology based on optimally modified log-spectral amplitude (OM-LSA) algorithm is used. According to the enhanced LDV-captured speech, a GMM-UBM model is built to recognize remote speaker. The experiment results show that the average EER using LDV-captured speech is 16.9590%. These results show great promise of using LDV for long range speaker recognition applications.

All-fiber laser Doppler vibrometer (LDV) systems have great potential in the application of remote acoustic detection. However, the system performance is impaired due to the serious intermediate frequency (IF) crosstalk signal, which is caused by the fiber circulator. In this paper, a system adopting a partial-fiber structure is proposed and analyzed. Simulative and experimental analysis indicate that the IF crosstalk signal is mainly caused by the fiber circulator, and it damages demodulation signal. In order to reduce the IF crosstalk signal, a polarization prism is employed to substitute the circulator. Experimental results reveal that the IF crosstalk signal can be eliminated by the partial-fiber LDV effectively. The comprehensible speech signals within the range of 50m can be obtained.