AI and Voice predictions for 2022
Wednesday, January 5, 2022
Scott Stephenson, CEO and co-founder of Deepgram, tells us his AI and Voice predictions for 2022 like how users will prefer well-documented API's since they will make speech recognition easier to implement, and how AI-powered automatic speech recognition can be leveraged for sophisticated use cases.
Scott Stephenson is a dark matter physicist turned Deep Learning entrepreneur. He earned a Ph.D. in particle physics from the University of Michigan where his research involved building a lab two miles underground to detect dark matter. Scott left his physics post-doc research position to found Deepgram. Stephenson talks about his 2022 predictions and what’s next in AI and voice.
Every business has a unique speaker base of multiple languages, dialects, genders. In 2022, we will see companies expand beyond English-only speech recognition into additional languages, depending on customers’ geography.
Users will opt for best of breed APIs over all-in-one big-box solutions
Not only will we see languages expand, but customers will also look to customized solutions that address specific product names and use cases. As a result, builders of voice-enabled experiences will prefer well-documented APIs with robust onboarding tools, as they will make speech recognition easy to implement and customize according to their business goals.
From Compliance to Cash Cow
In 2021, companies utilized automatic speech recognition (ASR) primarily for operational efficiency, compliance, and regulatory mandates. Due to the ongoing pandemic, shift to remote work and digital-first experiences, we saw an appetite from companies looking to leverage ASR for more sophisticated use cases that had the power to increase company revenue (e.g., real-time analytics use cases).
AI and Voice Predictions
In 2022, we expect to see more enterprises expanding beyond batch into real-time use cases. Companies will look to AI-powered ASR to gain valuable customer and employee insights in real-time, rather than waiting days or weeks for a less accurate transcription to be available. This will allow them to quickly address valuable feedback and improve company performance, leading to increased revenue and customer satisfaction overall. Furthermore, with AI-powered ASR, enterprises won’t have to trade accuracy for speed or lower costs.
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