Husam Ali Abdulmohsin1,*, Hala Bahjat Abdul Wahab2, Abdul Mohssen Jaber Abdul Hossen3
Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 339-355, 2022, DOI:10.32604/iasc.2022.018045
- 03 September 2021
Abstract Classification is the last, and usually the most time-consuming step in recognition. Most recently proposed classification algorithms have adopted machine learning (ML) as the main classification approach, regardless of time consumption. This study proposes a statistical feature classification cubic spline interpolation (FC-CSI) algorithm to classify emotions in speech using a curve fitting technique. FC-CSI is utilized in a speech emotion recognition system (SERS). The idea is to sketch the cubic spline interpolation (CSI) for each audio file in a dataset and the mean cubic spline interpolations (MCSIs) representing each emotion in the dataset. CSI interpolation… More >
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