face.sentiment
Perceived emotion recognition that detects a range of facial expressions like happiness, contempt, neutrality, and fear.
AI-based facial expression analysis mimics our human coding skills quite impressively as it captures raw, unfiltered emotional responses .
audio.sentiment
To better understand your customers’ view of your products & services, you can implement audio sentiment analysis into your research channels. Our algorithm automatically transform an audio file into written text that can be further analyzed.
Sentiment analysis on conversational audio data can be classify in three categories: positive, negative or neutral.
text.sentiment
Sentiment analysis performed on textual data is a natural language processing (NLP) technique used to help businesses monitor brand and product sentiment in customer feedback, or to a better understanding of customer needs.
Using AI, our solution can pick up cues that indicate the sentiment attached to a segment of text, showing whether the content is happy, sad, or evokes any other sentiment the model is trained to recognize.
