One area where we can clearly see this is in conversational intelligence platforms, which use AI to optimize communications and business processes.
Conversational intelligence solutions are used across sales teams, analytics teams, and more. But how, specifically, are these platforms using AI?
To understand the modern state of AI in conversational intelligence, we can examine how those platforms are using AI technology today and the latest advancements in the technology behind it.
Speech-to-Text
Speech-to-text technology lies at the very core of conversational intelligence – everything else comes from there.
When you feed a conversation to an AI-powered tool, speech-to-text technology converts the conversation into written words. The transcripts are then fed to the AI-powered tools, where they can be analyzed and understood.
This means that the speech recognition technology needs to be as accurate as possible. Every word matters, as missing or changing even a single word in a sentence can completely change its meaning. However, speech recognition technology often has difficulty understanding different languages or accents, not to mention dealing with background noise and cross-conversations, so finding an accurate speech-to-text model is essential.
For a good example of accurate and powerful speech-to-text technology, we can look at Universal-1 from AssemblyAI. Universal-1 is trained on 12.5 million hours of multilingual audio data and is designed to account for conditions like background noises, accents, and language switching, making it incredibly accurate. This latest Speech AI model is helping organizations build and improve conversational intelligence platforms.
"The Universal-1 model from Assembly AI is doing a great job at powering some of our core services, including meeting notes, tasks, and Semblian, our AI meeting chatbot. Its high quality multi-language capability aligns well with our global product footprint, supporting over 40 languages including dual language use in meetings. We are also impressed with the speed improvements, which have been especially impactful on our long duration workloads." – Artem Koren, CPO and Co-founder of Sembly AI
Generative AI
Beyond Speech-to-Text, Generative AI is one of the biggest trends in artificial intelligence technology today. We can see generative AI used to create more natural-sounding conversational AI, such as chatbots and virtual agents, as well as empowering employees for everyday work.
Generative AI is now being used to help employees draft emails and responses, as well as automatically log calls with detailed notes. For example, contact centers will use speech-to-text technology to transcribe conversations. After the transcription is made, generative AI is used to assist contact center agents and sales reps in real-time by providing automated coaching and suggestions.
Essentially, generative AI is being used to make conversational intelligence platforms more efficient, intelligent, and natural sounding.
Automated Summaries
One of the most common and helpful features of conversational intelligence platforms is the ability to automatically understand and summarize meetings and conversations. This uses natural language understanding and speech-to-text to not only transcribe the conversation but also to understand it and generate notes and summaries.
