Abstract
This paper presents an algorithm for recognition of emotions in speech by extracting features such as formants, Perceptual Linear Prediction coefficients, Mel-Frequency Cepstral Coefficients, Bark Frequency Cepstral Coefficients, energy, pitch and standard deviation. The classifiers implemented are K-Nearest Neighbors (KNN), Linear Support Vector Machine (SVM), Quadratic SVM, Bagged Tree Ensemble and Quadratic discriminant. The paper presents a comparative study on the different classification techniques that can be used to distinguish between various emotions present in human speech. A comparison in terms of testing accuracy obtained using these classifiers has been performed in this paper on a database created for 4 emotions viz. anger, joy, sorrow and neutral in Marathi language.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
