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We are at a true cusp of innovation within all aspects of our life. From shopping to communication, we all rely on technology to make our life easier. There has never been a more critical time to place customers' needs first. With current events, banking has never been more vital, and with a substantial shift in user behavior, the technology that supports customers must also transform and adapt. Those that fail to stay up to speed means losing customers to the competition.

Is it possible to diagnose COVID-19 simply by the sound of someone's voice? A consortium of researchers and businesses is guessing it just might be. Launched this past spring by voice assistant developer Voca.ai and Carnegie Mellon University, the group has gone international with the recent addition of Brazilian biometrics startup Unike Technologies. The idea of the COVID Voice Detector project is "to use a suitably trained AI to analyze the probability that someone is infected with the coronavirus based on the sound of their voice and cough. The online test asks users for some basic health information and anything they know about if they may have been exposed. The result is scored for lung health and the potential presence of COVID-19."

In the fight against COVID-19, several artificial intelligence labs are turning to an unexpected piece of evidence that might help diagnose the illness: people's voices. A team of researchers from Harvard and MIT is using machine learning to comb through voice recordings from COVID-19 patients and healthy people in an attempt to identify specific vocal signatures that could indicate someone is carrying the virus. A similar project is underway at Carnegie Mellon University's CyLab. Research is still in early stages, but the teams aim to develop AI tools that could tell people whether they have coronavirus based on an audio recording of their voice. If proven successful, the tools could allow more people to choose to self-isolate even if they don't have access to a COVID-19 test.

First things first: what is TTS? TTS or Text-to-Speech technology converts text into spoken speech. If you know Siri or those handy voice GPS directions on smartphones, then congratulations! Since 1000 AD, humans have strived to create synthetic speech, but it didn't enter the mainstream until the mid 1970s – early 1980s when computer operating systems began implementing it. Walt Tetschner, leader of the group that produced DECtalk in 1983, explains that while the voice wasn't perfect, it was still natural sounding and was used by companies such as MCI and Mtel (two-way paging).

Researchers from the Max Planck Institute for Intelligent Systems, a member of NVIDIA's NVAIL program, developed an end-to-end deep learning algorithm that can take any speech signal as input – and realistically animate it in a wide range of adult faces. "There is an extensive literature on estimating 3D face shape, facial expressions, and facial motion from images and videos. Less attention has been paid to estimating 3D properties of faces from sound," the researchers stated in their paper. "Understanding the correlation between speech and facial motion thus provides additional valuable information for analyzing humans, particularly if visual data are noisy, missing, or ambiguous." The team first collected a new dataset of 4D face scans together with speech.