Abnormal sound analytical surveillance system using microcontroller

Teng, Tan Teng; Sze, Lim Tien; Yeng, Ong Lee

doi:10.1109/cspa.2016.7515824

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Tan Teng Teng et al [36] have proposed to use microcontroller embedded system to enhance current CCTV system. Proposed abnormal sound embedded system is to carry out the sound detection, audio processing and analysis.…”

Section: Security Based Surveillance Systemmentioning

confidence: 99%

CCTV Surveillance System, Attacks and Design Goals

Muthusenthil¹,

Kim²

2018

IJECE

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Closed Circuit Tele-Vision surveillance systems are frequently the subject of debate. Some parties seek to promote their benefits such as their use in criminal investigations and providing a feeling of safety to the public. They have also been on the receiving end of bad press when some consider intrusiveness has outweighed the benefits. The correct design and use of such systems is paramount to ensure a CCTV surveillance system meets the needs of the user, provides a tangible benefit and provides safety and security for the wider law-abiding public. In focusing on the normative aspects of CCTV, the paper raises questions concerning the efficiency of understanding contemporary forms of ‘social ordering practices’ primarily in terms of technical rationalities while neglecting other, more material and ideological processes involved in the construction of social order. In this paper, a 360-degree view presented on the assessment of the diverse CCTV video surveillance systems (VSS) of recent past and present in accordance with technology. Further, an attempt been made to compare different VSS with their operational strengths and their attacks. Finally, the paper concludes with a number of future research directions in the design and implementation of VSS.

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Section: Security Based Surveillance Systemmentioning

confidence: 99%

CCTV Surveillance System, Attacks and Design Goals

Muthusenthil¹,

Kim²

2018

IJECE

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“…We name this kind of interference as speaker-specific noise in unseen environment. To be specific, we first accomplish the speech decomposition using the Dual-Tree Complex Wavelet Transform (DT-CWT) [12], locate the inferences in each sub-speech signal, and aggregate them to reconstruct the noise-like interference with the constraint of typical human voice frequency range approximately in 100-4000 Hz [13]. The final augmented speech can be expressed as the superposition of the raw one and the noise-like interference.…”

Section: Introductionmentioning

confidence: 99%

Speech Augmentation via Speaker-Specific Noise in Unseen Environment

Guo

Zhao

et al. 2019

Interspeech 2019

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Speech augmentation is a common and effective strategy to avoid overfitting and improve on the robustness of an emotion recognition model. In this paper, we investigate for the first time the intrinsic attributes in a speech signal using the multi-resolution analysis theory and the Hilbert-Huang Spectrum, with the goal of developing a robust speech augmentation approach from raw speech data. Specifically, speech decomposition in a double tree complex wavelet transform domain is realized, to obtain sub-speech signals; then, the Hilbert Spectrum using Hilbert-Huang Transform is calculated for each sub-band to capture the noise content in unseen environments with the voice restriction to 100−4000 Hz; finally, the speechspecific noise that varies with the speaker individual, scenarios, environment, and voice recording equipment, can be reconstructed from the top two high-frequency sub-bands to enhance the raw signal. Our proposed speech augmentation is demonstrated using five robust machine learning architectures based on the RAVDESS database, achieving up to 9.3 % higher accuracy compared to the performance on raw data for an emotion recognition task.

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Abnormal sound analytical surveillance system using microcontroller

Cited by 2 publications

References 7 publications

CCTV Surveillance System, Attacks and Design Goals

CCTV Surveillance System, Attacks and Design Goals

Speech Augmentation via Speaker-Specific Noise in Unseen Environment

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