Assignment- Moods & Emotions of Music Lover
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Added on 2019-10-01
Assignment- Moods & Emotions of Music Lover
Added on 2019-10-01
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Emotion detection media player using 3 differentalgorithms1
Table of ContentsChapter 1: Introduction....................................................................................................................31.1 Background of the paper........................................................................................................31.2 Aim of the research................................................................................................................41.3 Objectives of the research......................................................................................................41.4 Research questions.................................................................................................................41.5 Significance of the paper.......................................................................................................51.6 Problem statement.................................................................................................................51.7 Research limitation................................................................................................................61.8 summary................................................................................................................................61.7 structure of the research project.............................................................................................7Chapter 2: Literature review............................................................................................................82.1 Emotion detection of human..................................................................................................82.2 Facial expression based music player....................................................................................82.3 Edge detection music player................................................................................................102.4 Support Vector Machine or SVM........................................................................................12Chapter 3: Research Methodology................................................................................................163.1 Introduction..........................................................................................................................163.2 Research Philosophy............................................................................................................163.3 Research Approach..............................................................................................................173.4 Research design...................................................................................................................173.5 Data collection process........................................................................................................183.6 Data analysis modes............................................................................................................19Chapter 4: Data analysis................................................................................................................20Face detection coding in python using webcam........................................................................202
Edge detection algorithm...........................................................................................................22Chapter 5: Conclusion and Recommendation...............................................................................30References......................................................................................................................................323
Chapter 1: Introduction1.1 Background of the paper Music has some important role in enhancing the life of a person because it is a highly significantrelaxation medium for music followers as well as listeners. Now a day, the music technology isvery improved and the music listener uses this improved technology such as local playback,multicast stream, reverse, and other facilities. The listeners are satisfied with these factors andplay music based on their mood as well as behaviour. Audio feeling recognition provides list ofmusic that is supported to various mood and emotions of music lover. Various categories ofemotions and audio signal that is received, is classified by audio felling recognition. To exploresome features of audio, AN signal is used and MR is used to extract various important data fromthe AN signal of audio. The listener is trying to set their playlist according to their mood.However, it consumes more time. Various music players provide different kinds of features suchas proper lyrics with singer name and all. In this system, the arrangement of playlist is reactedbased on listener’s emotions to save the time for manually storing playlist.The best way to express emotion and mood of person is the facial expression and physicalgesture of human. This system is used extract facial expression and based on this expression thesystem automatic generate playlist that is completely matched with the mood and behaviour oflisteners. This system consumes less time, reduces the cost hardware and removes the overheadsof memory. The face expression is classified into five different parts like joy, surprise,excitement, anger and sadness of human. To extract important, related data from any audiosignal, high accurate audio extraction technology is used with lesser time. A model of emotion isexpressed to classify the song into seven types such as unhappy, anger, excitement with joy, sad-anger, joy, surprise. The emotion-audio module is combination of feeling extraction module andmodule of audio feature extraction. This mechanism provides a more huge potentiality and goodreal-time performance rather than recent methodology. Various kinds of approaches are used toprocess the edge detection of an image such as mouse, speech reorganization using AI andothers. In this case, three algorithms are used these are used like edge detection, face detectionand SVM. The edge detection algorithm helps to reduce computation of processing any largeimage. Face detection algorithm provides high accuracy to detect object as well as image. This4
algorithm is very fast in nature. This system can extract emotion and mood of human and theystarted communication with human being. This system is used to sense facial expression ofhuman and based on this facial expression it arranges the playlist for human. Human does notneed to select their playlist based on their mood or emotion. Computer can communicate withhuman beings like talking, reacting and extracting human emotion, automatically guess thefeelings of human beings. The emotion detection develops new technology in recent years toprocess various images, interaction between humans and machines and machine learning. Now aday, emotion detection plays a vital role in neuroscience, computer science, medical and othervarious purposes. To make rational decisions, interaction with social media, emotion detection isvery important. This system can understand what listener wants to listen to according to theircurrent state of mind. 1.2 Aim of the research The aim of the research is to understand the functioning of the three algorithms used in order todevelop the Emotion detection Media player.1.3 Objectives of the research The objectives of the research are listed below:To play the song automatically based on human emotions and feelings.To discuss three algorithms for detecting the emotion of humansTo communicate with the people and extract the gesture and mind state of peopleTo discuss the impact of three algorithms on emotion detection media playerTo develop proper algorithm for recognizing human emotionTo develop the appropriate system as per the human emotion this is used to identifyhuman gestures using some technology.1.4 Research questionsHow to play the song automatically as per the listener’s mood?What is main purpose of the three algorithms to detect emotion of human?How to extract the people's emotions and gestures of humans using media player?What are the impacts of thee algorithms on emotion detection media player?How to develop appropriate algorithm for detecting emotion?5
How to develop appropriate media player to extract emotion of human?1.5 Significance of the paperThe importance of emotion detection media player is looking forward to the emotion of usersand it is used to detect human emotion. This system helps to play music automatically byunderstanding the emotion of humans. It reduces the time of computation and searching time forhuman. Memory overhead is reduced by this emotion detection media player. The systemprovides accuracy and efficient results for detecting gestures of humans. It recognizes the facialexpression of people and arranges suitable playlist for them. It mainly focuses on the features ofthe detected emotion rather than actual image. Here, listener does not want choose any song fromthe playlist automatically. There are no requirements for any playlists. The music lovers do notwant to categorize the song according to their gestures, mental state and feelings. Here SVMalgorithm is used to classify and analyse the regression. It uses hyper-plane for doing this. It isused to access image with the help of computer devices such as mouse and various computernetworks. It mainly detects the digital image through the video. It classifies data as per theirbehaviour and features. Data is transformed by using this technique and according to thiscollected data set; it set some boundaries among the promising outcomes. Another algorithm isedge detection algorithm. In any image the edge parts are the basic thing. The edge is the set ofseveral pixels. The detection of edge is one of the best techniques to extract the edge of animage. The output of this algorithm is expressed by the two-dimensional function. The thirdalgorithm that is used for emotion detection is the face recognition. The main advantage of thisalgorithm is to identify the actual emotion of human beings by their facial expressions such asjoy, sadness, anger and other emotions. The algorithm is mainly responsible to reduce thecomputation time for detecting the facial expression of any person.1.6 Problem statementThis is difficult task for music lover to create and segregate the manual playlist among the hugenumber of songs. It is quite impossible to keep the track of large number of song in the playlist.Some songs that are not used for long time waste lot of space and listener have to delete this kindof song manually. Listeners have some difficulties to identify the suitable song and play the songbased on variable moods. Now a day, people cannot automatically change or update the playlistin a easiest way. Listener has to update this playlist manually. The list of playlist is not equal all6
time as per the listener requirement. It changes frequently. So there is no such system to reducethese kinds of problems.1.7 Research limitationIn this research, there are some limitations to the used methodologies. Three types of algorithmsare used to design the system. There are some chances to use two or more algorithms to make thenew developed system efficient. However, this process takes more cost for using thesealgorithms. It is very much time consuming task because of the processing of each algorithm in avery efficient way. For this reason, it is big limitation for this research. If the research gets muchtime and cost then the research will be very effective and the new improved system will moreaccurate to give the actual output.1.8 summaryChapter 1 depicts the background of the Emotion detection media player. The aim of thisresearch is to understand the functioning of the three algorithms used to develop the Emotiondetection Media player. The main objective of the research is to develop a new system to detectthe human emotion and based on this emotion this system generates the lists of songautomatically. For this reason, the system uses three algorithms. Edge detection algorithm is usedto detect the edge of the digital image, face detection algorithm is used to detect the facialexpression of the human, and SVM is used to classify the detected image as per the features andbehaviour.7
IntroductionLiterature ReviewMethodologyData Analysis and FindingsConclusion and Recommendations1.7 structure of the research project8
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