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Singer Separation for Karaoke Content Generation 27

Singer Separation for Karaoke Content Generation

引用

27th Conference on the Oriental COCOSDA International Committee for the Co-Ordination and Standardisation of Speech databases and Assessment Techniques, O-COCOSDA 2024

作者： Lin, Hsuan-Yu Chen, Xuanjun Jang, Jyh-Shing Roger Graduate Institute of Networking and Multimedia National Taiwan University Taipei Taiwan Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan National Taiwan University Dept. of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798331506032

Due to the rapid development of deep learning, we can now successfully separate singing voice from mono audio music. However, this separation can only extract human voices from other musical instruments, which is undesirable for karaoke content generation applications that only require the separation of lead singers. For this karaoke application, we need to separate the music containing male and female duets into two vocals, or extract a single lead vocal from the music containing vocal harmony. For this reason, we propose in this article to use a singer separation system, which generates karaoke content for one or two separated lead singers. In particular, we introduced three models for the singer separation task and designed an automatic model selection scheme to distinguish how many lead singers are in the song. We also collected a large enough data set, MIR-SingerSeparation11, which has been publicly released to advance the frontier of this research. Our singer separation is most suitable for sentimental ballads and can be directly applied to karaoke content generation. As far as we know, this is the first singer-separation work for real-world karaoke applications. © 2024 IEEE.

关键词： Source separation

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Context-Aware Neural Video Compression on Solar Dynamics Observatory 22

Context-Aware Neural Video Compression on Solar Dynamics Obs...

引用

22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Khoshkhahtinat, Atefeh Zafari, Ali Mehta, Piyush M. Nasrabadi, Nasser M. Thompson, Barbara J. Kirk, Michael S. F. Da Silva, Daniel West Virginia University Dept. of Computer Science & Electrical Engineering WV United States West Virginia University Dept. of Mechanical & Aerospace Engineering WV United States Nasa Goddard Space Flight Center MD United States

ISBN: (纸本)9798350345346

NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's daily activity. data compression is crucial for space missions to reduce data storage and video bandwidth requirements by eliminating redundancies in the data. In this paper, we present a novel neural Transformer-based video compression approach specifically designed for the SDO images. Our primary objective is to efficiently exploit the temporal and spatial redundancies inherent in solar images to obtain a high compression ratio. Our proposed architecture benefits from a novel Transformer block called Fused Local-aware Window (FLa Win), which incorporates window-based self-attention modules and an efficient fused local-aware feed-forward (FLaFF) network. This architectural design allows us to simultaneously capture short-range and long-range information while facilitating the extraction of rich and diverse contextual representations. Moreover, this design choice results in reduced computational complexity. Experimental results demonstrate the significant contribution of the FLaWin Transformer block to the compression performance, outperforming conventional hand-engineered video codecs such as H.264 and H.265 in terms of rate-distortion trade-off. © 2023 IEEE.

关键词： FLaWin Neural Video Compression Solar Dynamics Observatory Swin Transformer

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Facial Emotional Recognition Using Convolutional Neural Network

Facial Emotional Recognition Using Convolutional Neural Netw...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Deepak Raj Md. Abdul Wassay Dept. of Computer Science Chandigarh University Mohali India Dept. of Computer Science Engineering Chandigarh University Mohali India

The face of a person is his identity. Most of his emotions, issues can be derived from his face. Face is the window to the soul which was said by famous French doctor Duchenne de Boulogne. He used several techniques to support his theory like giving shocks of electric impulses to understand how a person reacts to muscular contractions. He also tried to induce some of the expressions of bizarre looking. The ultimate aim is to analyze how much muscles contribute to emotion. He successfully derived lots of human emotions which is hidden. After 200 years this field is still active as it requires more experiments to extract invisible truths of human truths. Lots of Emotion Recognition which is automatic have been seen in the field of Marketing and Advertising. It is also seen in the field of Medical, Law and order$\ldots$etc. The main fundamental question arrives whether it is good to enter into our personal space. This a question which has lots of dimension. Those who are against this practice is claiming that this is a violation of human rights by which we can use the stored data to harm the society in future. Even though it is a major concern if we can rectify the above the scope in this area is phenomenal. Lots of researchers are still working on this area because of mainly one reason that is its wide application in the area of Medical science. It can be used by a doctor for diagnosing a person with certain psychological disorders, children with Autism, person with Parkinson’s disease. It can be widely used to diagnose children with Autism so that particular child can be motivated at early stage leads to his success in future and thus provide a good citizen to the society. In our research we are using several datasets such as FER2013, CK+$\ldots$etc. These datasets have been given to a model which includes Deep Convolutional Neural Network. Here input image is given to a model using camera. The particular image has to done preprocessing to extract fine features in th

关键词： Emotion recognition Pediatrics Autism Technological innovation Face recognition Psychology Medical services

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Principles of Machine Learning in Voice Recognition 2

Principles of Machine Learning in Voice Recognition

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2nd International Conference on data Analytics, Computing and Artificial Intelligence, ICDACAI 2023

作者： Jiang, Tianyang Zhu, Yuke Feng, Haojun University of Shanghai for Science and Technology Usst Dept. School of Optical-Electrical and Computer Engineering Shanghai China Zhejiang Gongshang University Dept. School of Information and Electronic Engineering Hangzhou China Jurong Country Garden School Jurong China

ISBN: (纸本)9798350339765

Sounds carry a huge amount of information of our daily life and physical events. We hear sounds in complex environment and from increased amounts of electric devices, so audio recognition is definitely an important technology in human-computer interaction. In recent years, speech recognition technology developed rapidly. Summarizing recognition methods is necessary when there are too many methods to choose. This paper introduces some of the advanced technologies, Recurrent Neural Network, Convolutional Neural Network, Linear Regression, Multilayer Perceptron, Random Forest and their principle. © 2023 IEEE.

关键词： Recurrent neural networks

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A Comprehensive Review for Optimizing the Design of Cluster Head Selection to Enhance the Network Lifetime in WSN

A Comprehensive Review for Optimizing the Design of Cluster ...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： S Bhuvaneswari A Abirami R P Suvetha Sri R Srinithy R Swathi Faculty of dept. of Computer Science and Engineering Easwari Engineering College Chennai India Student of dept. of Computer Science and Engineering Easwari Engineering College Chennai India

Large numbers of cooperative sensor nodes make up wireless sensor networks (WSNs). Sensors are the integral component in WSN IoT. Sensors separate and organize in the clusters by similar characteristics. A cluster head is in charge of gathering information from the nodes in every cluster and transmitting it to its base station (BS). Because every node are powered by batteries, lessens energy usage and elongating lifetime of network are crucial concerns for WSN. The primary goals of this analysis are to address issues that previous writers have not addressed and to provide beginning researchers with a fundamental understanding of how to choose cluster head (CH) based on various methodologies. To designate a node as CH, some enhancing parameters are chosen, such as residual energy, packet transmission rate, throughput, distance between BS and Cluster Node (CN), and betweenness centrality. data packets are transferred using the optimized protocol to reduce delay time and increase transmission rate after many CH are chosen. Analysis of the many literatures was done. An Optimization Algorithm is needed to enhance network lifetime from this analysis. A comparison of various algorithm based on the features and difficulties from the analysis is done. There are many drawbacks, such as a cluster head is chosen at random, data transmission rate is not considered, no proper formation of clusters, importance for load and temperature is not given, stability is not taken into account. Thus, there is a need for optimized algorithm to overcome all the mentioned issues.

关键词： Wireless communication Wireless sensor networks Temperature distribution Clustering algorithms Throughput data models Delays

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Movie Genre Prediction Using AI-Generated data and Natural Language Processing

Movie Genre Prediction Using AI-Generated Data and Natural L...

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International Conference on computer and Information Technology (ICCIT)

作者： Sifat Tanvir Ayesha Parpia Abontee Md. Abu Rayhan Md. Fuadur Rahman Tasnim Sultana Ajwa Ahmed Dept. of Computer Science and Engineering Brac University Dhaka Bangladesh Dept. of Computer Science Brac University Dhaka Bangladesh

Every movie belongs to one or more specific genre. In this work, a dataset was prepared consisting of AI-generated movie titles and plots of 10 different genres. Text vectorization was used to convert every single word of the titles and plots into vectors. These vectors were used to predict which genre each movie belongs to. For training, a sequential neural network model was built and used, and an accuracy of almost 80% was achieved.

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APC System: A system for the Blind and Deaf Who Face Visual and dept. Perception Challenges

APC System: A system for the Blind and Deaf Who Face Visual ...

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Recent Advances in science and engineering Technology (ICRASET), International Conference on

作者： Suraya Mubeen G.V. Ashritha Sanjeev Bandru Marri Sireesha Nuthanakanti Bhaskar Voruganti Naresh Kumar Dept. of Electronics and Communication Engineering CMR Technical Campus Hyderabad Telangana India Dept. of Computer Science and Engineering (Data Science) CMR Technical Campus Hyderabad Telangana India Dept. of Information Technology Sreenidhi Institute Of Science And Technology Hyderabad Telangana India Dept. of Computer Science and Engineering CMR Technical Campus Hyderabad Telangana India

In this paper, APC System (Assistive Path Control System) is proposed to provide blind and deaf individuals with the assistance they need to navigate their environment by using the "third eye" technology. As part of the technology, a hand glove and a stick are used to identify obstacles using ultrasonic sensors and to provide haptic feedback through vibrations in order to detect obstacles. Wearers of the glove are alerted through a buzzer and provided with feedback on distance and direction of obstacles in their path, while those of the stick are given feedback on the change in elevation and dept. over time. The use of vibrations as a form of feedback is crucial to the functioning of deaf people. Testing of the technology has shown promising results, and future work will focus on optimizing accuracy and accessibility by using machine learning algorithms in order to improve the system. As a primary goal of the APC System is to enhance the quality of life for blind and deaf individuals by providing them with a tool that will help them navigate their environment in the most effective manner.

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6G Enabled Smart IoT in Healthcare System: Prospect, Issues and Study Areas 1

6G Enabled Smart IoT in Healthcare System: Prospect, Issues ...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Matre, Priti Vivek Kumbhare, Ashish Gedam, Ravi Sharma, Animesh Vaishnav, Naveen Kumar Naidu, Dileep Yashwantrao Chavan College of Engineering Dept. of Information Technology Maharashtra Nagpur India The Icfai University Faculty of Science and Technology Chhattisgarh Raipur India G H Raisoni University Department of Computer Science and Engineering Madhya Pradesh Saikheda India

ISBN: (纸本)9798350330915

The Internet of Medical Things, (IoMT) requires extensive and intelligent connection, enormous bandwidth, minimal latency, extremely high data rates, and enhanced healthcare experiences. In contrast to the current 5G wireless systems, the next 6G communication system is anticipated to offer Smart IoMT (SIoMT) solutions all over at any moment to enhance people's quality of life. The conceptual structure of 6G networks, their integration with multifaceted networking technologies like wireless optical networks, cell-free communication systems, and quantum telecommunications, in addition to the decentralised protection framework in the context of SIoMT, are presented in this paper. A novel concept for linking households to hospitals, healthcare personnel, healthcare supplies, healthcare facilities etc. will be enabled by such low latency and ultra-high-speed communication networks. The paper also discusses the obstacles and future research directions of installing SIoMT, as well as the needs of 6G wireless networking along with additional important critical approaches. © 2023 IEEE.

关键词： 5G wireless network 6G communication system distributed security Internet of Everything (IoE) Internet of Healthcare Things machine learning Quantum communication

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To Predict the Fire Outbreak in Australia using Historical database 10

To Predict the Fire Outbreak in Australia using Historical D...

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10th International Conference on Reliability, Infocom Technologies and Optimization ,Trends and Future Directions, ICRITO 2022

作者： Tayal, Devendra Kumar Agarwal, Nidhi Jha, Anjali Deepakshi Abrol, Vrinda Indira Gandhi Delhi Technical University for Women Dept. of Computer Science & Engineering New Delhi India

ISBN: (数字)9781665474337

ISBN: (纸本)9781665474337

Australian bush fires have caused huge damage, not only to the environment but also to the community. In southeastern Australia, 11.5 million hectares (28.4 million acres) of bushland and forest was affected during the 'Black Summer' Bushfire of 2019-2020. The frequency of bushfires gives context for modelling different climate data to accurately anticipate future hot regions for bushfires. In this study, we have implemented a Machine Learning based Decision Tree Model to construct a Forest Fire Prediction Model using data from the last 20 years. This algorithm is derived from a collection of unrelated decision trees. Additionally, we converted observed fire spots into a continuous density of fire spots and made a choropleth map. The prediction model's structure makes it possible to produce predictions with a higher degree of accuracy. Additionally, it helps to increase assistance for fire crews at the front-line. © 2022 IEEE.

关键词： Fires

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Hybrid Software Reliability Prediction Model Using Feature Selection and Support Vector Classifier 4

Hybrid Software Reliability Prediction Model Using Feature S...

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4th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2022

作者： Rath, Suneel Kumar Sahu, Madhusmita Das, Shom Prasad Mohapatra, Srikanta Kumar C. V. Raman Global University Dept. of Computer Science Engineering Odisha Bhubaneswar India Birla Global University Dept. of Computer Science Engineering Odisha Bhubaneswar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9781665400732

The primary purpose of the software industry is to provide high-quality software. Software system failure is caused by faulty software components. The goal of reliable software is to reduce the amount of software programme failures. Software defect prediction is a crucial aspect of developing high-quality software. One can predict software failures by implement essential prediction metrics and previous fault information. A good software fault prediction model makes testing easier while also improving the quality and consistency of software. For defect prediction systems based on diverse parameters, several methodologies have been proposed. However, none of the models meet the criteria for software reliability defect prediction. So in this article we proposed a hybrid software reliability model using feature selection and support vector classifier. In terms of software reliability defect prediction, the provided methodology is acceptable for different software metrics with experimental approvals utilizing a standard dataset. In the methodology, the NASA Metrics data Program datasets are used for real-time verification and validation. © 2022 IEEE.

关键词： Forecasting

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