What is a voice call sentiment analysis?

Sentiment analysis technology uses machine learning and natural language processing (NLP) to help understand or interpret human sentiments based on voice pitch, behavioral patterns, and facial expressions.

How does sentiment analysis work in voice calls?

Sentiment analysis records human-spoken speech, converts the speech into text, runs machine learning and NLP algorithms, and classifies the call as positive, negative, or neutral in real time.

Is voice sentiment analysis ethical?

It depends on maintaining transparency by Informing participants about the analysis, obtaining explicit consent to record and analyze calls, and ensuring sensitive information is secure and compliant with privacy laws.

What are the technologies used in Voice call sentiment analysis?

Natural language processing (NLP), speech analytics, machine learning, and deep learning are some of the technologies used in voice call sentiment analysis tools.

What factors are analyzed in voice sentiment analysis?

Keywords, phrases, language sentiment, tone, pitch, speed, volume, overall flow, and the intention of the conversation are some factors that need to be analyzed for sentiment analysis in voice calls.