About the technology

Talking is a natural way for people to interact with each other. Small children can speak long before they can read, write, or type. People can carry on a conversation even when they’re busy doing other tasks. The introduction of virtual assistants like Amazon’s Alexa, Apple’s Siri and Google’s assistant have brought voice interfaces to the mainstream as a way for people to communicate with devices. These are popular with customers who love the ease with which they can be used. Voice holds the promise of providing a frictionless way to interact with computers, and organisations are looking for ways to take advantage.

Imagine you work for a late-night comedy show and want to put together a montage of news anchors saying the word "covfefe". You could employ an army of interns to listen to hundreds of hours of recorded broadcasts, or you could use Cobalt's Telefol engine to search.  Technology to the rescue!

Understanding Keyword Spotting

Many companies and organizations have access to large volumes of recorded speech, but it can be challenging to leverage the full value of that wealth of information because it is costly and time-consuming to search through audio.  One strategy is to use automatic speech recognition to transcribe the audio, then search the transcript. The "covfefe" example illustrates one limitation of that approach--because it's not a word in the English lexicon, the transcript would not include it.

Virtual assistants allow us to interact with technology by voice. They are built on a complex pipeline of AI technology that understands the breadth and complexity of spoken language. This pipeline includes automatic speech recognition, natural language understanding, dialogue management and text-to-speech components. The technology in the pipeline is based on machine learning - a subset of AI algorithms that learn their behaviour from data instead of being explicitly programmed.