Journal of Software Engineering & Software Testing (ISSN: 2457-0516)

Journal of Software Engineering & Software Testing

The Journal of Software engineering & Software Testing deals with the application of engineering to software that includes documenting the requirements of the software through application of basic design principles. The journal also emplasizes to analyze and design alternatives keeping in mind the utility of the finished product and whether the final product meets its requirements. At the same The journal also emphasizes on the safety, reliability, cost-affectivity and functional aspects of the software.

Some of the topics covered under this journal (but not limited to them) are:

    • Mathematics
    • Chemistry
    • Basic Engineering
    • Computer Literacy
    • Physics Laboratory
    • Engineering Graphics
    • Biology for Engineering
    • Principles of Environmental Science
    • Material Science
    • Digital Computer Fundamentals
    • Computer Organization and Architecture
    • Data Structures and Algorithms
    • Software Engineering Principles
    • Object Oriented Programming
    • Microprocessors
    • Software Design
    • Computer Skills
    • Discrete Mathematics
    • Computer Networks
    • Industrial management and economics
    • Software quality management
    • Web technology

Vol 4, No 3 (2019): Emotion Detection during Call Using Artificial Intelligence

Authors:-Prof.SirdeshPande S.A, Bobade Ankita Sukhadeo, Dargude Dipali Vitthal, Kharat Monali Sampat, Gawade Ashwini Madhukar

Abstract:-The analysis of human speech is a very challenging research area as it concerns the detection of user communities. Emotions play an initial role in human interaction. The ability to understand human emotions by analyzing voice is desirable in different applications of speech recognition in emotions can be found in different areas, such as the interaction between computers and humans and call centers. Previously, emotion recognition made use of simple classifiers on bag-of-words models. However, the existing work of emotion recognition on Voice was carried out with the help of deep learning techniques on static voice data. The proposed method focuses on increasing the overall accuracy of emotion recognition during calls using artificial intelligence. The overall aim is to accurately recognize the various emotions that a particular speech expresses semantically.

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