Speech To Emotions Detection

Gayatri Ravjibhai Parmar

Speech To Emotions Detection

Authors: Gayatri Ravjibhai Parmar

Unique Paper ID: 151653
Volume: 8
Issue: 1
PageNo: 462-468

Keywords: Voice Detection Signal Processing Mood identification Machine Learning Visualization

Abstract:
Detection of mood and behavior by voice analysis which helps to detect the speakerâ€™s mood by the voice frequency. Here, I aim to present the mood like happy, sad and behavior detection device using machine learning and artificial intelligence which can be detect by voice analysis. Using this device, it detects the userâ€™s mood. Moreover, this device detects the frequency by trained model and algorithm. Algorithm is well trained to catch the frequency where it helps to identify the mood happy or sad of the speaker and behavior. On the other hand, behavior can be predicting in form, it can be either positive or negative. So, this device helps to prevent mental health issues and used in medical and gaming testing. Furthermore, it is easy to identify personâ€™s mood by their expression and by their actions on daily activities. But it is effective challenge to detect mood and behavior by voice frequency because rich environment affects the most. Thus, this device works as signal processing. Moreover, Machine learning, Data visualization and Data warehousing helps to discover the concepts and installation of database, while machine learning used to train the model and data visualization represent effective visualization of overall result from the data. Thus, these modules help to develop the basic and advanced concepts as well as research for this project

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ISSN: 2349-6002
Volume: 8
Issue: 1
PageNo: 462-468

Speech To Emotions Detection

Available:https://ijirt.org/Article?manuscript=151653

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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