Speech Sentiment Analysis Based on Basic Characteristics of Speech Signal

Abstract

As the pace of life continues to accelerate, people’s life pressure is increasing. With the accumulation of time, people’s mental and psychological conditions have been affected to a certain extent. These mental illnesses will not cause any impact under normal circumstances, but once they break out, they will cause trauma that cannot be ignored in life or even in society. Therefore, we hope to design a system program that can chat with humans in daily life, and it can feel the human’s emotional changes in daily conversations. When humans have negative emotions, it can comfort us in time and even warn humans when our negative emotions reach a certain limit. When humans have positive emotions, it can give humans affirmative approval and encouragement. Based on this concept, we must first analyze the different emotions that humans design in daily conversations. This article is mainly based on the basic characteristics of audio signals to judge the user’s emotional changes. The database we use is six different emotional voices recorded by four voice actors, and each voice contains 50 single sentences for emotional recognition analysis. keywords: Voice emotions analysis, Voice feature value, Voice speed