Conversational intelligence tools and artificial intelligence technology have always been tightly intertwined. The core challenge of conversational intelligence is to extract meaningful insights from large amounts of unstructured conversation data, and AI technology has long been the most effective way of doing so. Because of this, advances in AI capabilities result in new opportunities in the conversational intelligence space.
In the last few years especially, there has been an extraordinary rise in the capability and accuracy of AI systems to analyze voice, video and text data. Specifically concerning conversational intelligence, there are advances in three major areas that have created new possibilities.
1. Automated speech recognition.
2. Understanding and transformation of unstructured text.
3. Emotional analysis of video.
Automated speech recognition (ASR) refers to the technology used to transcribe spoken language into text. ASR relies on algorithms that analyze the acoustic characteristics of speech, such as pitch, tempo and phonetic content, to convert it into a digital format that can be processed by machines.
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