Xihai Xie
ABSTRACT
The accuracy and efficiency of sound event recognition are affected by the accuracy of endpoint detection. In a complex environment, it is difficult to detect the endpoint of a sound event due to the influence of background noise. Aiming at the sound events in the elevator operating environment, this paper analyzes and studies multiple characteristic parameters based on short-term energy, short-term average zero-crossing rate, and cepstral distance, and proposes a new characteristic parameter, namely multiple cepstral distance, which is adopted after adding a smoothing mechanism. The new decision mechanism performs endpoint detection. This paper collects environmental sounds of elevators in schools, communities, and shopping malls, and conducts endpoint detection comparative experiments on four sound events: speech, explosion, glass breaking, and alarm sound under different signal-to-noise ratios. The experimental results show that the method can be well adapted to the endpoint detection of four sound events in different environments. Even in the -5dB environment, the average misdetection rate of the four sound events can still be lower than 10%, and the method is robust Better, it has a wide range of application prospects in an elevator safety inspection.
- Defu Wang. Real-time Human Intrusion Detection Using Audio-visual Fusion[D]. Shanghai Jiaotong University.2012:1-7.Google Scholar
- Xie, C., Cao, X.L. and He, L.L. (2012) Algorithm of Abnormal Audio Recogniton Based on Improved MFCC. Procedia- Engineering, 29, 731-737. https://doi.org/10.1016/j.proeng.2012.01.032Google ScholarCross Ref
- Hongrui Zhang, Xiurong Ma, Yunlong Shan. Abnormal Sound Detection Method of Trains Running at Stations[J]. Computer Applications and Software. 2019,36(08):130-137=171.Google Scholar
- Ziao Xiong, Yan Cang. The Voice Activity Detection for Oink in Fattening Pig Houses[J]. Applied Science and Technology. 2020,47(05):79-85.Google Scholar
- Haoge Yang, Chengli Sun. Research of Aircraft Engine Sound Recognition Method Based on GMM-UBG[J]. Computer Science and Application. 2017,7(8):781-787.Google ScholarCross Ref
- Jing Li, Nongliang Sun, Shenghua Teng. State Identification Algorithm for Substation Devices Based on Sound Recognition[J]. Information Technology. 2015(06);94-98.Google Scholar
- Minlei Xia. Research on Speech Endpoint detection technology[C]. Hangzhou: Zhejiang university. 2005:11-20.Google Scholar
- Huang Z K, Zhang X B, Zhu Y Q. A new improved energy-zero entropy speech endpoint detection with low signal-to-noise ratio[J]. Microelectronics & Computer, 2020, 37(6): 19-23.Google Scholar
- Zhang Y, Wang K, Yan B. Speech endpoint detection algorithm with low signal-to-noise based on improved conventional spectral entropy[C]. 2016: 3307-3311.Google Scholar
- Tan Z H, Lindberg B. Low-complexity variable frame rate analysis for speech recognition and voice activity detection[J].IEEE Journal of Selected Topics in Signal Processing, 2010,4(5): 798-807.Google ScholarCross Ref
- Prabakaran D.,Sriuppili S.. Speech Processing: MFCC Based Feature Extraction Techniques- An Investigation[J]. Journal of Physics: Conference Series,2021,1717(1).Google Scholar
- Oh Yangki, Kang Minwoo, Lee Kwangchae, Kim Sunkuk. Construction Management Solutions to Mitigate Elevator Noise and Vibration of High-Rise Residential Buildings[J]. Sustainability,2020,12(21).Google Scholar
- R Ab Uske T , Fernandes J . A 12-bit SAR ADC with background self-calibration based on a MOSCAP-DAC with dynamic body-biasing[C]// IEEE International Symposium on Circuits & Systems. IEEE, 2016.Google Scholar
- Wang Juan. Research Status and Future Development of Endpoint Detection Algorithms Based on Computer Science Language Signals[J]. Journal of Physics: Conference Series,2021,1744(3).Google Scholar
- Chang J H. Warped discrete cosine transform – based noisy speech enhancement[J]. IEEE Trans on Circuits and Systems-II: Express Briefs, 2003,52(9) : 535-539.Google ScholarCross Ref
Index Terms
- Research on Endpoint Detection of Sound Events in Elevator Operation Environment
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