Sentiment analysis for customer's reviews using hybrid approach

One of the greatest challenges to human-machine interaction is estimating the speaker's emotion. The need is for clear, more accurate information about consumer preferences has led to increasing interest in high-level analysis of online media context. In this paper, I have proposed an approach for emotion recognition based on both speech and media content. Most of the existing approaches to sentiment analysis focus on audio and text sentiment. The novelty in this approach is the generation of text sentiments, audio sentiments and blend them to obtain better accuracy.