The current digital era is bombarded with the vast amount of information because of the usage of internet by people in everyday life. Natural language processing (NLP) is evolving everyday with advancements in various applications to understand and analyze the languages. Text summarization is one of the applications of NLP. Due to the scarcity of time, text summarization is a boon which generates the concise, relevant description of large information. Language processing models have advanced in English language but is lagging in other regional languages. Kannada is one of the oldest Dravidian languages with rich literacy and legacy and one of the prominent languages of south India which is spoken by 60 billion people across the world. Limited work in NLP has been carried out in this language. This proposed model works for abstractive text summarization on Kannada language using convolutional neural network (CNN) and long short-term memory network (LSTM) methods. To the best of our knowledge, this work presents the first implementation of abstractive text summarization on this language and achieved F1-score of 0.88.