Showing posts from 2017

Improving Real Time Communications with Machine Learning

When we talk about the applications of Artificial Intelligence / Machine Learning (AI/ML) for Real Time Communications (RTC) we can group them in two different planes: Service Level : There are many features that can be added to a videoconference service, for example identification of the participants, augmented reality, emotion detection, speech transcription or audio translation .  These features are usually based on image and speech recognition and language processing. Infrastructure Level : There are many ways to apply ML that do not provide new features but improve the quality and/or reliability of the audio/video transmission. Service level applications are fun, but they are more for Product Managers and I like technology more, so in the next sections I will try to describe possible applications of AI/ML for Real Time Communications at Infrastructure Level organizing those ideas in five different categories. Optimizing video quality Some of the ML algorithms used fo