Translating Sentimental Statements Using Deep Learning Techniques

Natural Language Processing (NLP) allows machines to know nature languages and helps us do tasks, such as retrieving information, answering questions, text summarization, categorizing text, machine translation. To our understanding, no NLP was used translate statements from negative sentiment positive with resembling semantics, although human communication needs. The developments of translating sentimental using deep learning techniques are proposed in this paper. First, for a translation model, we create negative–positive statement datasets. Then techniques, the model is developed. Perplexity, bilingual evaluation understudy, evaluations experiments test results satisfactory. Finally, if trained datasets can be constructed planned, believe possible, more sophisticated models