AACEM: Automatic Annotation and Classification of Emotions for mixed-codes

This paper presents a framework for automatic creation of an emotions-labeled dataset specifically designed for short texts written in a blend of Roman Urdu and English, and addresses the inherent absence of distinct structure in Roman Urdu language. The software development is carried out in two key phases. During the first phase, cleaning and automatic annotation of raw text is performed and in the second phase, classification of emotions along with prediction is carried out. The developed software significantly simplifies the process of dataset creation by employing natural language processing (NLP) techniques, tailored for the mixed-codes.