Underwater Vehicle Noise Source Recognition Using Structure Dynamic Adjustable SVM

Getting calls for ransoms are common phenomena in kidnapping and abduction related incidents where the life of the victim remains extremely vulnerable. These phone calls are often analyzed in real-time by law enforcement authorities to quickly identify the suspects and get crucial information for quick action. However, it is often difficult to manually analyze those phone calls due to the quality of sounds and the presence of several background noises. Even with much high-end software in their inventory, it is futile to accurately refine the incoming calls as it takes a huge amount of time to declutter the different layers of noises in the call. This paper proposes a model based on deep convolutional neural network and signal processing for automatic classification of crucial sounds in ransom related phone calls. We have proposed LSTM and 2D CNN customized models and compared their outputs with VGG16 and AlexNet. Moreover, this paper also presents a unique dataset of different sounds in terms of voices like male or female and the environmental sounds where the victim might be in which can be a probable clue for investigation purposes consisting of 17650 audio clips collected from verified online sources. Finally, the models produced very high classification accuracy with the accuracy of LSTM reaching around 93.4%.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Underwater Vehicle Noise Source Recognition Using Structure Dynamic Adjustable SVM

Cited by 2 publications

References 6 publications

An Adaptive FCM Probabilistic Neural Networks with Confidence Criteria

An Adaptive FCM Probabilistic Neural Networks with Confidence Criteria

RansomListener: Ransom Call Sound Investigation Using LSTM and CNN Architectures

Contact Info

Product

Resources

About