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.
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.
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).
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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