Modelling the machines’ language with natural language processing and machine learning algorithms

Language is one of the most important elements communication for people and all living things. A large number studies have been conducted in literature on formation languages natural language processing processes. It has observed that these contain differences terms analysis, approach method. In study, a model proposed machines to create their own as contribution literature. With this point view, it contributed idea efficiency processes will increase by communicating with each other like humans. aim developing an produce languages, aimed distinguish sounds things classifying them generate new using convolutional deep neural network applied alphabet was decided system. next step, Regenerative Artificial Neural Networks were used together Mel Frequency Cepstral Coefficient Dynamic Time Warp methodologies similar named respective sounds. Unlike studies, visual data which converted from audio files obtained Kaggle open repository "Audio Cats Dogs" dataset. addition, supported CNN networks achieve effective performance.