How Deep Learning Can Address Your Video Streaming Challenges?

May 20, 2021
4 min read

After an exhausting day at work, you are damn tired but still want to catch up on your favourite shows. And, exactly when you’re on the verge of an intriguing scene, your video has paused. It then suffered a buffer, then never resumed at all. After a few frustrating minutes later, you had to experience a video in its lowest resolution hardly showing any clarity.

How Did An Exhilarating Engagement Turn Into A Disastrous One?

Say hello to the complexities of video streaming. But this is not how a video streaming experience should be. That's when game-changing technologies like AI and Deep Learning come into play. They will guarantee high-definition, zero-delay, enhanced streaming OTT, improving the user experience and making it more fun and worthwhile.

Adaptive BitRate

Every week, OTT (Over the Top) content creators and providers release new and exciting content. However, one major drawback of OTT platforms is that they have not been able to address adequately is quality of experience, also known as QoE.

The overall resolution of a video, startup time, stalls, and delays that occur are factors that affect the QoE. Video distribution is heavily reliant on internet speed, or bandwidth, which can have a significant impact on the user experience. This is where the Adaptive BitRate helps solve the problems with a unique algorithm.

With insufficient bandwidth, in earlier days, a video completely stopped streaming. But today, any type of unpredictable bandwidths are handled seamlessly with ABR.  The output of your network has dynamically "adapted" the parameters of a video. As a result, the video's quality has been compromised. But, it continues to play by reducing the resolution instead of stopping the relay. However, internet speed remains a factor. It's 2021, and there's a lot of chatter about Deep Learning that we need to focus on.

Intelligent Solutions

Videos have become the latest form of data communication, serving as a natural extension of email or text messages. This has necessitated advancements in video streaming, as well as network and storage optimization.

The majority of what is going on these days is unperceptive to the material it contains. A scene in which the actors are simply conversing has a different bitrate than an action scene. Imagine being able to see Dumbledore's wrinkles as he lifts his wand but being unable to see Harry battle Voldemort.

And to do so, you'll need to know the answers to the following questions.

  • What if the substance of a scene could be deciphered?
  • What if streaming algorithms learned the quality of experience for each scene?
  • What if all frames are given relative importance in the encoding?
  • What if the streaming is device-agnostic?

Deep Learning is the only possible solution to address these problems of video streaming.

Deep Learning

Deep Learning and Artificial Intelligence are developing technologies to increase video content and user quality of experience. Content-aware AI has the potential to significantly enhance the viewing experience by making it more personalized, interactive, and novel. Device-aware DNN (Deep Neutral Network) can be created by dynamic computation with strategic resources that can scale up the performance of streaming.

When the encoder looks at the whole video rather than the pixels in individual frames, it is a clever and noticeable way to improve QoE. This is beneficial for

  • A stronger grasp of the content
  • Streaming of the best possible standard
  • Identifying redundancies in content.

The Impact of Deep Learning

Device Awareness

The quality of the device has a significant impact on the entire decoding process. Making it device friendly ensures that people can watch it at any time, from any place, on any device. Even with a simple tap on the application of their smartphones as the smartphones are the latest computers, after all. Knowing which device the user is using will make his or her personal experience more engaging. A device's innate power can be used as its soul potential to reshape the entire streaming experience.

Context-Awareness

Being device-aware isn't the end of the story. Deep Learning as well as Artificial Intelligence can be trained to pay close attention to the video's overall context, search preferences, and genre preferences. For example, a user can stream a specific series weekly. Deep learning will use this information to show the user their favourite show, related genres, and other works by the director and cast. This not only increases the user's QoE but can also benefit OTT providers.

But First, Understand the Streaming Business

Why does an OTT platform need to invest in such user-friendly technologies? A recent survey of 1000 customers in Urban India who use OTT streaming provides the answer to this query. When using the OTT, as many as 62% of people experience problems such as pausing, buffering, and the app hanging while using it. Also, the issues were faced on specific devices where the same OTT was flexible to stream on a laptop but nor adaptable to a smartphone. And the streaming was affected majorly during travel.

Customers are expressing their disappointment with OTT services more than ever by leaving immediate reviews on official and social media pages. This demonstrates a strong intolerance for lower QoE, which can harm sales. Long load times, pixelation, buffering, and stalled videos are no longer acceptable in this industry.

Emerging patterns, as well as the pandemic situation, have brought online streaming new dynamics. The boundaries between short films and fiction videos have widened to include gaming, live sports streaming, and the release of movies. As a result, more revenue is generated.

Playing on personal computers was a thing of the past. However, games like PUBG have attracted larger audiences simply by using a smartphone. Stadia, Google's latest gaming platform, announced that a low bandwidth of 25mbps is sufficient for exceptional streaming.

This demonstrates how cost-effective ideas for changing the phase of this sector using AI and deep learning are evolving. According to a new survey, 53.98% of viewers will be able to switch to premium subscriptions for interesting content with few streaming issues.

Conclusion

Finally, the big picture of providing high-quality videos at lower subscription costs to produce more sales is visible. Many practical issues have been solved as a result of the significant benefits gained from the use of AI and the role of deep learning in creating a better streaming experience. DNN-based developments are the most significant advances in this method. So, very soon, all populations will be shifted to unrivalled QoE and amazing video consumption.