Emotion Analysis Using Speech

Krupashree M M, Naseeba Begum, N. Priya, N. S, Rashmi Motkur
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Abstract

The main goal of our project is to identify the emotions a speaker evokes when speaking. For example, utterances uttered in states of fear, surprise, excite-ment, anger, or joy are loud and fast and have a large and wide pitch range, whereas utterances uttered in states of depression or fatigue are slow and deep. This is us We use deep learning techniques to build models that can identify human emotions through the analysis of speech and language patterns. The main reason for choosing this project is that speech sentiment analysis has become one of the largest commercialization strategies in which client moods and dispositions play a large role. Therefore, there is an increased demand for products or companies to recognize an individual’s emotions and recommend appropriate products or assist him accordingly. It can also be used to monitor status. More recently, speech recognition and analysis have also been applied to medicine and forensics.
语音情感分析
我们项目的主要目标是识别说话者在说话时唤起的情绪。例如,在恐惧、惊讶、兴奋、愤怒或喜悦的状态下发出的声音响亮而快速,音调范围又大又宽,而在抑郁或疲劳的状态下发出的声音则缓慢而低沉。我们使用深度学习技术来建立模型,通过分析语音和语言模式来识别人类的情绪。选择这个项目的主要原因是,语音情感分析已经成为最大的商业化策略之一,其中客户的情绪和性格发挥了很大的作用。因此,越来越多的产品或公司需要认识到个人的情绪,并相应地推荐合适的产品或提供帮助。它还可以用于监视状态。最近,语音识别和分析也被应用于医学和法医学。
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