Sentiment Analysis of Music using Statistics and Machine Learning PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Sentiment Analysis of Music using Statistics and Machine Learning PDF full book. Access full book title Sentiment Analysis of Music using Statistics and Machine Learning by Aakash Mukherjee. Download full books in PDF and EPUB format.

Sentiment Analysis of Music using Statistics and Machine Learning

Sentiment Analysis of Music using Statistics and Machine Learning PDF Author: Aakash Mukherjee
Publisher: Sanctum Books
ISBN: 8195293174
Category : Music
Languages : en
Pages : 78

Book Description
Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.

Sentiment Analysis of Music using Statistics and Machine Learning

Sentiment Analysis of Music using Statistics and Machine Learning PDF Author: Aakash Mukherjee
Publisher: Sanctum Books
ISBN: 8195293174
Category : Music
Languages : en
Pages : 78

Book Description
Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.

Cognitive Analytics: Concepts, Methodologies, Tools, and Applications

Cognitive Analytics: Concepts, Methodologies, Tools, and Applications PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799824616
Category : Science
Languages : en
Pages : 1961

Book Description
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.

Music Emotion Recognition

Music Emotion Recognition PDF Author: Yi-Hsuan Yang
Publisher: CRC Press
ISBN: 143985047X
Category : Computers
Languages : en
Pages : 251

Book Description
Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with

Deep Learning Techniques for Music Generation

Deep Learning Techniques for Music Generation PDF Author: Jean-Pierre Briot
Publisher: Springer
ISBN: 3319701630
Category : Computers
Languages : en
Pages : 303

Book Description
This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.

Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017

Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017 PDF Author: Fernando De la Prieta
Publisher: Springer
ISBN: 9783319615776
Category : Computers
Languages : en
Pages : 0

Book Description
PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2017 in the special sessions: Agent-Based Social Simulation, Modelling and Big-Data Analytics (ABM); Advances on Demand Response and Renewable Energy Sources in Agent Based Smart Grids (ADRESS); Agents and Mobile Devices (AM); Computer vision in Multi-Agent Robotics (RV); Persuasive Technologies (PT); Web and Social Media Mining (WASMM). Thevolume also includes the papers accepted for publication in the Doctoral Consortium (DCAI, DCAI-DECON, ISAMI, MIS4TEL, PAAMS, PACBB 2017 conferences).

Sentiment Analysis

Sentiment Analysis PDF Author: Bing Liu
Publisher: Cambridge University Press
ISBN: 1108787282
Category : Computers
Languages : en
Pages : 451

Book Description
Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.

Text Mining with R

Text Mining with R PDF Author: Julia Silge
Publisher: "O'Reilly Media, Inc."
ISBN: 1491981628
Category : Computers
Languages : en
Pages : 193

Book Description
Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.

Statistical Analysis of Folk Songs of Jharkhand

Statistical Analysis of Folk Songs of Jharkhand PDF Author: Shivani Tiwari
Publisher: Sanctum Books
ISBN: 8195293166
Category : Music
Languages : en
Pages : 66

Book Description
Folk songs play a very significant role in Indian classical music as the root of Indian classical music is the Indian folk music itself. Different states have different folk songs. This work deals with the statistical analysis of the folk songs of Jharkhand. Each song's analysis concerns with verifying whether the probabilities of notes in the song are fixed throughout the song or are the note probabilities varying. This tells us whether the probability distribution followed by the notes is multinomial or quasi multinomial respectively. Statistical parameterization method is used to quantify melody and rhythm. The presence of rhythm and melody is also analyzed by the Inter Onset Interval (IOI) and note duration graphs. The book should be found useful by music researchers and students of music and musicology, ethnomusicologists and music enthusiasts.

Advances in Data and Information Sciences

Advances in Data and Information Sciences PDF Author: Shailesh Tiwari
Publisher: Springer Nature
ISBN: 9811952922
Category : Technology & Engineering
Languages : en
Pages : 558

Book Description
This book gathers a collection of high-quality peer-reviewed research papers presented at the 4th International Conference on Data and Information Sciences (ICDIS 2022), held at Raja Balwant Singh Engineering Technical Campus, Agra, India, on May 6 – 7, 2022. The book covers all aspects of computational sciences and information security, including central topics like artificial intelligence, cloud computing, and big data. Highlighting the latest developments and technical solutions, it will show readers from the computer industry how to capitalize on key advances in next-generation computer and communication technology.

Smart Computing and Self-Adaptive Systems

Smart Computing and Self-Adaptive Systems PDF Author: Simar Preet Singh
Publisher: CRC Press
ISBN: 100050994X
Category : Computers
Languages : en
Pages : 289

Book Description
The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth. Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.