Speech emotion recognition using support vector machines

• Main Authors: Africa, Aaron Don M., Tabalan, Anna Rovia V., Tan, Mharela Angela A.
• Format: text
• Published: Animo Repository 2020
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1096; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2095/type/native/viewcontent
• Institution: De La Salle University

© 2020, World Academy of Research in Science and Engineering. All rights reserved. The technology of recognition is one that has been developed continuously over the years and with its various applications in a wide variety of fields opens up massive opportunities to bridge the gap between humans and computers. Albeit common knowledge that computers are designed to make everyday life easier, there is still an indubitable lack of deep understanding due to the computer’s lack of knowledge in complex emotions present with human beings and this often prohibits computers to offer specific help that is suitable for its user. Therefore, it’s important to further develop today’s technology and one promising way to accomplish this task is to utilize Speech Recognition to recognize and classify emotions as well. This way, the computer essentially understands the user enough to give valuable aid instead of just preset actions. Support Vector Machine is one of the leading classifying algorithms in today’s time, boasting the highest accuracy rate which makes it the most viable option for this field of study.