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Deepfake Detection of Singing Voices With Whisper Encodings

Deepfake Detection of Singing Voices With Whisper Encodings

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Falguni Sharma Priyanka Gupta Centre for Artificial Intelligence Banasthali Vidyapith Jaipur India Dept. of Communication and Computer Engineering The LNM Institute of Information Technology Jaipur India

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The deepfake generation of singing vocals is a concerning issue for artists in the music industry. In this work, we propose a singing voice deepfake detection (SVDD) system, which uses noise-variant encodings of open-AI’s Whisper model. As counter-intuitive as it may sound, even though the Whisper model is known to be noise-robust, the encodings are rich in non-speech information, and are noise-variant. This leads us to evaluate Whisper encodings as feature representations for the SVDD task. Therefore, in this work, the SVDD task is performed on vocals and mixtures, and the performance is evaluated in %EER over varying Whisper model sizes and two classifiers-CNN and ResNet34, under different testing conditions.

关键词： Industries Deepfakes Signal processing Encoding Acoustics Noise robustness Speech processing Testing

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A Review on Iris Recognition Using Machine Learning Techniques

A Review on Iris Recognition Using Machine Learning Techniqu...

引用

Advanced Computing Technologies and Applications (ICACTA), International Conference on

作者： Yashwant S. Ingle Parikshit N. Mahalle Shraddha R. Khonde Suvarna Bhagwat Mandar P. Diwakar Dept. of AI&DS Vishwakarma Institute of Information Technology Pune India Dept. of Computer Engineering MESCOE Pune India

An iris is round in shape and colored part of a person’s eye. Iris’s characteristics are unique in every person, and therefore, it distinguishes one person from others. Several recognition systems exist in the biometric verification system, like face, voice, Iris, and finger. But Iris has a crucial role in authenticating or recognizing a human being. Generally, the iris recognition arrangement is associated with specific top expensive applications where security is paramount and uses a delicate infrared illumination camera to capture images. Even in the same person, the texture of the left and right eye is not similar. It differs even among the twins’ eyes, making it an extra secure way to automatically identify a person than other recognition systems. In the review paper, we highlight several existing iris datasets on iris recognition. Moreover, image preprocessing processes and segmentation techniques can be practically used to iris datasets and feature extraction methods, which will be used as input for any machine learning technique to identify the individuals efficiently.

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VascularVision: Mixed Reality Based Teaching and Learning Environment for Cardiovascular Conditions

VascularVision: Mixed Reality Based Teaching and Learning En...

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Advancements in Computing (ICAC), International Conference on

作者： Hashith Nissanka Sajini Wijayasundara Jude Rajarathne Sahan Vidanagamage Didula Thanaweera Arachchi Pradeep K. W. Abeygunawardhana Dept. Information Technology Sri Lanka Insitute of Information Technology Kandy Sri Lanka Dept. Information Technology Sri Lanka Insitute of Information Technology Colombo Sri Lanka Dept. Information Technology Sri Lanka Insitute of Information Technology Malabe Sri Lanka Dept. Computer Systems Engineering Sri Lanka Insitute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Developments in Augmented Reality (AR) and Virtual Reality (VR) have the potential to revolutionize medical education, especially in the areas of Coronary Angiography and Cardiac Auscultation. By giving medical and nursing students realistic, interactive experiences, the suggested VR and AR settings seek to modernize medical education by addressing the issues regarding the lack of real-world practice. Interactive 3D models, such as a realistic virtual body, rotatable heart models, ECG recordings, and real-life heart sounds, are available in the VR Cardiac Auscultation Environment. With the use of these components, students can practice diagnosing diseases including bradycardia, tachycardia, and cardiac murmurs in a dynamic and risk-free setting, improving their diagnostic skills. Similar to this, the AR Cardiac Auscultation Application combines interactive quizzes, machine learning for diagnostic verification, and real-time ECG scans to provide a powerful tool for teaching students how to recognize and understand various heart diseases and noises, this also can be a verification tool for junior doctors. By giving students firsthand experience with intricate medical procedures, virtual reality and augmented reality platforms offer a compelling and realistic approach to medical education. According to the research, these instruments can greatly enhance diagnostic proficiency, which will ultimately result in better educational outcomes and more qualified healthcare workers.

关键词： Heart Solid modeling Three-dimensional displays Tachycardia Education Medical services Electrocardiography Medical diagnostic imaging Augmented reality Diseases

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Automated Bengali abusive text classification: Using Deep Learning Techniques

Automated Bengali abusive text classification: Using Deep Le...

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Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS), International Conference on

作者： Showni Rudra Titli Shimul Paul Dept. Electronics and Communication Engineering National Institute of Technology Calicut India Dept. Computer Science and Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh

In recent years, the breakdown of most human causes that hampers a large number of people is verbal abuse. The most noticeable fact is that most of the verbal abuse is made online by people behind the screen. While this problem has occurred with growing modern technologies, a modern solution is needed to solve the drawback. The growing rate of abusive comments and hate speech online is rapidly increasing on a large scale, and manual reports and corrections cannot help this critical situation. This proposed model introduces automation of the hate speech filtering process through deep learning. This work uses only Bengali datasets to find the real classification, as many Bengali and English mixed research works are available in this field. Using the intelligent automated classification of text comments in a limited resource-constrained language (example: Bengali) is critical for several reasons. This proposed system classifies 'Personal Offensive Text', 'Geographical Offensive Text', 'Religious Offensive text', 'Crime Offensive Text', 'Entertainment, Sports, Meme Tiktok, and others'. By combining two large datasets for this research and employing Bengali BERT, the best feasible outcome has been *** paper indicates the complete results of the combined two different datasets and classified into nine segments, while the proposed Bengali BERT models achieved the highest accuracy of 0.706 and a weighted f1 score of 0.705 in the identification and classification tasks.

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Feel Good AI: Voice-Enabled Emotion-based Music Recommendation System

Feel Good AI: Voice-Enabled Emotion-based Music Recommendati...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Anjali Sharma Shubham Vishwakarma Liya T Mathew Dept. of Computer Science and Engg JSS Academy of Technical Education Bangalore India Dept. of Civil and Engg Thakur College of Engineering and Technology Mumbai India Dept. of Electronics and Communication Engg Cochin University of Science and Technology Kochi India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

Feel Good AI is a novel effort committed to improving psychological well-being by means of methodically providing customized music suggestions that are in accordance with the user’s emotional state. By combining sophisticated recommendation algorithms with advanced technologies, most notably Convolutional Neural Networks (CNN) for facial emotion recognition, this project effortlessly develops innovative tech and empathetic emotional support. The users interact with an intuitive chatbot that generates unique music suggestions through the use of personalized conversations in which they are asked specific emotion-related inquiries. Beyond immediate relevance, incorporating AI-powered music curation to enhance positive emotional experiences for individuals, particularly those afflicted with dementia, is of greater significance. We live in a society where stress and mental health problems are prevalent. By combining problem-solving and emotional well-being, Feel Good AI offers evidence that technology can enhance the quality of life.

关键词： Emotion recognition Technological innovation Temperature Mood Refining Real-time systems Convolutional neural networks

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Multishot Adversarial Network Decoding

Multishot Adversarial Network Decoding

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Annual Allerton Conference on Communication, Control, and Computing

作者： Giuseppe Cotardo Gretchen L. Matthews Julia Shapiro Alberto Ravagnani Dept. of Mathematics Virginia Tech Blacksburg VA USA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven The Netherlands

We investigate adversarial network coding and decoding focusing on the multishot regime. Errors can occur on a proper subset of the network edges and are modeled via an adversarial channel. The paper contains both bounds and capacity-achieving schemes for the Diamond Network and the Mirrored Diamond Network. We also initiate the study of the generalizations of these networks.

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Dual-Domain Feature-Guided Task Alignment for Enhanced Small Object Detection

Dual-Domain Feature-Guided Task Alignment for Enhanced Small...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Fangrui Guo Junwei Wu Quan Zhang Dept. Master of Engineering University of California Los Angeles Los Angles USA Dept. Computer Science University of Liverpool Liverpool the UK Dept. School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Small object detection is a critical challenge in Unmanned Aerial Vehicles (UAVs) due to the limited pixel representation of small objects and the impact of successive pooling operations, which frequently results in the disappearance of small objects within intricate backgrounds. To tackle this issue, we propose the Small Object Enhancement Pyramid (SOEP) module, which first transforms feature representations (i.e., in the spatial domain) into the frequency domain to better capture small objects typically characterized by high-frequency components. These feature representations are then fused in the spatial domain using a frequency-based attention map, enhancing small object representations by integrating information from both complementary domains. Furthermore, we introduce a Task Aligned Head (TAH) that integrates classification and localization tasks interactively, reducing the misalignment that occurs when these tasks are learned independently, particularly in the context of small objects. Experimental results on the Visdrone dataset verify that our proposed method (D 2 FTA) outperforms the baseline method by 12.7%, 14.19% on mAP 0.5 and mAP 0.5:0.95 .

关键词： Location awareness Accuracy Frequency-domain analysis Object detection Transforms Signal processing Feature extraction Autonomous aerial vehicles Acoustics Speech processing

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Integrated and Intelligent Elder-Friendly E-commerce Framework using NLP Techniques

Integrated and Intelligent Elder-Friendly E-commerce Framewo...

引用

IEEE Students' Conference on Electrical, Electronics and computer Science (SCEECS)

作者： Sivasanjith G Mohan Prabhu N Hemaswathi S Rajkumar P Rajeshkannan C R. Dhivya Dept. of Information Technology KARE Krishnankovil India Artificial Intelligence and Data Science Indra Ganesan College of Engineering Tiruchirappalli India Dept. of Computer Science and Engg. Mount Zion College of Engg. and Tech. Pudukottai India Dept. of Computer Science and Engg. Suguna College of Engineering Coimbatore India Dept. of Information Technology M.Kumarasamy College of Engineering Karur India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

All over the world, the population of elderly people is increasing a lot. There needs to be special attention to the welfare of the elderly person to make them confident in their independent quality of living. In recent years, researchers have shown much interest in smart home automation for people who live alone without any human assistance. However, the purchase of medical drugs, diapers, etc., outside the house has to be fulfilled by their family members or caretakers. In most cases, it is not feasible, as the family members may stay long away from the elders. Purchasing online is easy; however, analyzing the best product requires knowledge in each e-commerce application for better quality at a low cost. This paper proposes an integrated and intelligent e-commerce framework to avoid the drawback of purchasing items online in a single window using the NLP technique. The proposed framework provides offers, discounts, star ratings, and product reviews by analyzing other customers’ review data and purchase patterns. It provides interactive data analysis at a single window for the ease of elderly persons. The performance of the proposed framework was evaluated by 120 elderly persons using a simple questionnaire with a statistical analysis of a sample purchase.

关键词： Drugs Sentiment analysis Reviews Statistical analysis Urban areas Stars Smart homes Electronic commerce Older adults Recommender systems

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Auto Disturbance Rejection Control Based on A Neural Network Predictive State Observer

Auto Disturbance Rejection Control Based on A Neural Network...

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International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Shengzhi Du BJ van Wyk NFS Nahri Chunling Tu Dept. Electrical Engineering Tshwane University of Technology Pretoria South Africa Dept. Computer Systems Engineering Tshwane University of Technology Pretoria South Africa

This paper addresses the auto disturbance rejection control (ADRC) for systems with time delay. ADRC is an effective control for most linear or nonlinear systems with noises and disturbances, because of its advantage on disturbance estimation and compensation. The extended state observer (ESO) is a critical component of ADRC. However, this observer is usually designed for systems without time delay. The time delay in a system could lead the ADRC unstable when the phase delay of the response cannot be ignored. This paper proposes a neural network based predictive state observer (NNPSO) to predict the response of systems with time delay. The simulation results validate the proposed method when systems with time delay are controlled.

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Ensuring Cloud Tenant Data Security and OptimizingDDoS Detection Efficiency through Trust-Based Filtering 5

Ensuring Cloud Tenant Data Security and OptimizingDDoS Detec...

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5th International Conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Agarwal, Ankit Gupta, Saurabh Swamy, G. Prasadu, G. Ahuja, Vandana Badhan, Ajay Kumar Mamodiya, Udit Department of Information Technology Dr. Akhilesh Das Gupta Institute of Technology & Management New Delhi India Department of Computer Science & Engineering Dr. Akhilesh Das Gupta Institute of Technology & Management New Delhi India Department of IT Sreenidhi Institute of Science And Technology Telangana India Dept. of CSE Swami Vivekanand Institute of Engineering and Technology Punjab Ramnagar India Department of Computer Science and Engineering Lovely Professional University Punjab India Department of Electrical Engineering Poornima University Jaipur India

ISBN: (纸本)9798400709418

Tenant data security has grown critical as more and more commercial enterprises use cloud services for data processing and storage. The present study endeavors to tackle the dual problems of preserving tenant data in the cloud and enhancing the effectiveness of detecting Distributed Denial of Service (DDoS) attacks. We provide a brand-new strategy called Trust-Based Filtering that incorporates trust measurements into the current cloud security framework. Our approach for data security is centered on access controls, encryption, and ongoing monitoring. Sensitive information is prevented from being accessed by unauthorized parties even in the case of a breach thanks to encrypted data storage. Based on trust scores, access controls are dynamically modified to grant genuine tenants more access privileges while limiting dubious entities. The dynamic trust model used by the Trust-Based Filtering system assesses cloud tenants' behavior by looking at their past interactions with the cloud environment. © 2023 ACM.

关键词： Denial-of-service attack

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