October 10, 2024
Comments Off on How AI is Enhancing WebRTC Video Conferencing Applications

As we continue to navigate the complexities of remote work and virtual interactions, the demand for seamless and engaging video conferencing experiences has never been greater. WebRTC has long been a key player in enabling real-time communication between participants, but recent advancements in Artificial Intelligence (AI) are taking these capabilities to new heights. 

In this post, we’ll explore the exciting ways AI is transforming WebRTC video conferencing applications—from media processing and transport to productivity-boosting features and innovative voice and video bots.

Elevating the WebRTC Media Pipeline

WebRTC video conferencing applications perform multiple steps to achieve communication between participants. These include obtaining, processing and transporting media data from one device to another. 

Think of this as a media pipeline that begins with light and sound going into your device’s camera and microphone and ending with its correspondent video and audio streams played on the rest of the participants’ devices.

AI is becoming another stage in this pipeline. Yet rather than being another brick in the wall, it is the cherry on the top of the cake. AI is enhancing both media processing and transport, and also introducing innovative features that enrich the overall experience.

Such improvements and features usually fall in one of the following categories:

  • Media processing and transporting
  • Productivity-enhancing technologies
  • Voice and video bots

Media Processing & Transporting

AI is boosting WebRTC’s media processing capabilities through features like noise reduction and background removal. Tools like RNNoise, Krisp SDK, and MediaPipe are being used to process audio and video streams before sending them through the peer connection.

The flow goes like this:

  • The GetUserMedia API provides a raw, unprocessed stream.
  • The unprocessed stream goes through an AI-based process running on device or on the cloud, depending on the tool.
  • The AI-based process produces a manipulated, processed stream that is sent through an RTCPeerConnection.

Furthermore, companies like Meta and Atlassian are adopting approaches based on Machine Learning models to refine their bandwidth estimation processes, optimizing how their real-time communication applications transport media.

Additionally, AI-powered codecs like Google Lyra and Microsoft Satin promise to achieve higher audio compression rates while maintaining quality. However, these are not available for WebRTC just yet.

Productivity-Enhancing Features

AI provides features drive efficiency, reduce manual workload, and enable more informed decision-making in business environments. These may include, but are not limited to: 

  • Real-time Translation
  • Transcription
  • Summarization 
  • Sentiment analysis
  • Captions
  • Subtitles

Implementing such features involve sending media to Speech-to-Text (STT) services like Amazon Transcribe or Symbl.ai Streaming API, and then to Large Language Models (LLMs) like OpenAI GPT or Meta Llama. This enables insights in the form of summaries, sentiment analysis, or responses to requests.

Large Multimodal Models (LMMs) promise to provide this same approach with reduced latency by directly injecting audio streams into the model without the need for STT services. 

As of writing this post, OpenAI has enabled beta access to its Realtime API, which allows developers to provide audio streams directly to its GPT-4o multimodal model. (A post about this feature is on its way 😀)

Voice & Video Bots

AI also supports voice and video bots that participate in WebRTC sessions and interact with the participants.

This is done using a similar approach as the one used for implementing assisting features. Only here, users are able to “talk” directly to an LLM model, which in turn generates direct responses to their requests.

These bots are also able to extract relevant information and perform tasks on behalf of the users, like updating account information or making reservations.

Video and Voice bots are also capable of joining a video conference session in a third-party platform, such as Google Meet or Microsoft Teams, using a separate headless browser or similar service.

Further reading on bots by our team:

Transforming Virtual Interactions With WebRTC and AI

As we’ve seen, AI is transforming the landscape of WebRTC video conferencing applications. By leveraging AI-powered tools and techniques, developers can create more engaging, efficient, and productive communication experiences. With advancements in media processing, assisting features, and voice & video bots, the possibilities are endless.

Are you ready to unlock the full potential of your WebRTC video conferencing application? At WebRTC.ventures, we specialize in implementing cutting-edge AI techniques and features that can transform your user experience. From media processing and assisting features to voice & video bots, our team of experts will work closely with you to design and develop a customized solution tailored to your specific needs. Contact us today, and let’s make it live!

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