Emotion Based Music Player - XBeats

Gupte, Aditya; Naganarayanan, Arjun; Krishnan, Manish

doi:10.22161/ijaers/3.9.30

Cited by 13 publications

(4 citation statements)

References 4 publications

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“…In literature, micro-expressions have been used to determine the mental status of patients with schizophrenia [2,22] to provide security against thieves and malicious people [1,5] and to detect pain for newborn babies [34,35]. Some studies use micro-expressions to detect drivers' fatigue and sleepiness [27], to predict safe driving behaviour [31], and to create automatic music playlists [13,26].…”

Section: Related Workmentioning

confidence: 99%

The influence of micro-expressions on deception detection

Yildirim

Chimeumanu

Rana

2023

Multimed Tools Appl

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Facial micro-expressions are universal symbols of emotions that provide cohesion to interpersonal communication. At the same time, the changes in micro-expressions are considered to be the most important hints in the psychology of emotion. Furthermore, analysis and recognition of these micro-expressions have pervaded in various areas such as security and psychology. In security-related matters, micro-expressions are widely used to detect deception. In this research, a deep learning model that interprets the changes in the face into meaningful information has been trained using The Facial Expression Recognition 2013 dataset. Necessary data is also obtained through live stream or video stream by detecting via computer vision and evaluating with the trained model. Finally, the data obtained is transformed into graphic and interpreted to determine whether the people are trying to deceive or not. The deception classification accuracy of the custom trained model is 74.17% and the detection of the face with high precision using the computer vision methods increased the accuracy of the obtained data and provided it to be interpreted correctly. In this respect, the study differs from other studies using the same dataset. In addition, it is aimed to facilitate the deception detection which is performed in a complex and expensive way, by making it simple and understandable.

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Section: Related Workmentioning

confidence: 99%

The influence of micro-expressions on deception detection

Yildirim

Chimeumanu

Rana

2023

Multimed Tools Appl

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“…Joy, sadness, anger, surprise, and fear also provides a highly accurate audio information retrieval method that can extract relevant information from audio signals in less time. 2.4 Automate the interaction -Parul Tambe et al [3] came up with an idea to automate the interaction between the user and the music player, knowing all the preferences, emotions and activities of the user and giving a selection of songs accordingly, the device records different facial expressions of the user to determine the mood of the user and thus predicting the genre of the music. The electrical activity of neurons in brain cells is recorded.…”

Section: Classification: Internalmentioning

confidence: 99%

Music Recommendation Based on Current Mood Using Ai & Ml

Roy¹,

CH²,

Kavya³

et al. 2023

Preprint

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Music always has a special connection to our emotions. It is a method of connecting people all over the world through pure emotions. When all of this is considered, it is exceedingly difficult to generalize music and state that everyone would enjoy the same type. Music recommendation based on mood is greatly needed because they will assist humans in relieving stress and listening to soothing music based on their current emotions. Its primary goal is to accurately predict the user's mood, and songs are played by the application based on the user's selection as well as his current mood. This bot recognizes human emotions from facial images using Human-Computer Interaction (HCI). The extraction of facial elements from the user’s face is another critical factor. We used the CNN Algorithm to accurately detect the user's face in the live webcam feed and to detect emotion based on facial attributes such as the arrangement of the user's mouth and eyes. There is also a questionnaire where we can directly select a good option.

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“…cascade technique Nikhil Determining the users' state of mind through facial expressions [3]. People often express their feelings through their facial expressions and gestures but most people express their feelings through their faces.…”

Section: Haarcascade Technique -Model Developed Using Haarmentioning

confidence: 99%

“…Automate the Interaction -Parul Tambe came up with an idea to automate the interaction between the user and the music player, knowing all the preferences, emotions, and activities of the user and giving a selection of songs accordingly, the device records different facial expressions of the user to determine the mood of the user and thus predicting the genre of the music [3].…”

Section: 4mentioning

confidence: 99%

Music Recommendation Based on Current Mood Using Ai & Ml

2023

JCTCSR

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Music always had a special connection with our emotions. It’s a way to connect people around the world through pure emotion. Yet, it is extremely difficult to generalize about music and say that everyone will like the same kind of music. The mood-based recommendation is very necessary because it can help people relieve stress and listen to calming music based on their current mood. Its main purpose is to accurately predict the user’s mood, and then play songs according to the user’s choice and current mood. It uses human-computer interaction (HCI) to recognize human emotions from facial images and extracts facial features from the user’s face. Whenever a person wishes to listen to a specific kind of music, he might be ending up hearing some other kind of music that doesn’t match his mood. So, the primary objective of our project is to address the major challenges that are faced by users while trying to listen to any music at random. In this paper, two approaches are proposed to overcome the above–mentioned challenges. The first approach is implementing a questionnaire model. The user will be required to respond to a series of questions in this model, and depending on his response, the mood will be determined, and music will be suggested. While the second approach involves designing a model to identify user emotions and then suggest music depending on the mood detected. However, if the user is not satisfied with the emotion captured, he will also have the choice to return to one of the two previously described models and continue the procedure. Our project aims at developing a user interactive and user–friendly model.

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Emotion Based Music Player - XBeats

Abstract: Abstract-

Cited by 13 publications

References 4 publications

The influence of micro-expressions on deception detection

The influence of micro-expressions on deception detection

Music Recommendation Based on Current Mood Using Ai & Ml

Music Recommendation Based on Current Mood Using Ai & Ml

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Emotion Based Music Player - XBeats

Abstract: Abstract-

Cited by 13 publications

References 4 publications

The influence of micro-expressions on deception detection

The influence of micro-expressions on deception detection

Music Recommendation Based on Current Mood Using Ai &amp; Ml

Music Recommendation Based on Current Mood Using Ai & Ml

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Music Recommendation Based on Current Mood Using Ai & Ml