Voice sentiment analysis involves the use of advanced algorithms to decipher and understand the emotional tone conveyed within spoken language.

By employing machine learning and natural language processing techniques, this technology can identify and categorize emotions such as happiness, sadness, anger, or neutrality based on the nuances in tone, pitch, rhythm, and intensity of the speaker’s voice.

Through this analysis, it becomes possible to gauge the sentiment behind conversations, enabling applications across various fields, from customer service to mental health support and beyond.