How Machine Learning is Changing Video Creation

The only constant thing around us is change, and the world is constantly changing. Today, new technology is being produced, or a new approach is being discovered to use the old technology. Machine Learning! is among the latest discoveries that can accelerate the process with a high-speed and bring-in personalised experience to its users. 

The basic science behind this technology? It collects data and learns the methods and algorithms that yield negative or positive results. It adapts itself following the data collected to bring continuous improvement and advancement to the system. 

A simple example of machine learning can be seen on our smartphones – The voice recognition system. The system adapts itself to the data collected from the user. With time it streamlines the process and continuously improves the system with more and more data collected to give the user a personalised experience. Moreover, machine learning can also be seen on social media platforms like Instagram and Facebook. The machine learning algorithms adapt themselves to the user’s frequently watched and searched data and curate a personalised list of ads and recommendations. 

But how is machine learning bringing a change in video creation?

With businesses being more and more technology-enabled, the usage of machine learning is also increasing. From e-commerce to entertainment and from security and fraud detection to financial trading – machine learning is integrated into every sector and industry to automate business activities and streamline them as per the user. 

One such place where machine learning has brought a change is video creation! From corporations to educational institutions that require live video. There are various situations and events with different settings, such as multi-camera or live streaming with a single-camera – where one can utilise machine learning applications. 

An industry which is ever-adapting itself is the software development market. Machine learning programs can be adapted from video editing tools to trim video tools and live streaming systems. 

Even though most of the applications are still theoretical and have only been tested in the labs, we are curious to know the advancement it will bring if adapted. We have listed machine learning applications that technicians and users can use to simplify and automate the video creation process are given below: 

• Virtual Production Studio: Imagine a virtual studio where humans and digital elements can integrate and create videos in the computer-automated surroundings and atmosphere. Through technical expertise and investment, one can streamline video creation. 

• Automated Optimization of Audio: In virtual video creation, one of the crucial things is having a clear and loud audio system. Without proper audio, the viewers cannot experience high-quality live-streaming or online lectures. Audio issues like distortion or trouble-shooting of the microphone may occur. To cure these issues, machine learning can fit into the picture. With tools, it can streamline the audio system and optimise it, allow the technicians to understand the occurrence of issues immediately, address them, and ensure that there is high-quality audio throughout the video creation process. 

• Abridged Videos: The process of editing and trimming video is long and tiresome. During video creation, there are tons of gaps, such as a change in settings or technical errors, which has to be removed by the technicians and editors during the post-production to bring in a polished final video for its release. Machine learning can automate and streamline the process by detecting the gaps and removing them. It will collect data or keywords for the gaps like the silence of more than 20 seconds or the disappearance of the moderator and remove them during post-production. This reduces the time consumption and accelerates the process of video creation. 

• Integration of Comments: The popularity of live streaming culture is increasing rapidly. Influencers and gamers are streaming on various platforms like YouTube, Facebook & other CDNs simultaneously, which allows viewers to watch and respond on platforms as per their comfort. This creates a problem for the moderator as people will comment on different platforms. To streamline this, machine learning applications can be used to aggregate the relevant comments of the viewer for the moderator to interact with & increase the engagement with the viewers. Machine learning collects data with positive results and keywords per the live stream and aggregates the comments across all the platforms. It may also automate and monitor the dynamic content and include it in the live streaming. 

• Highlight Reels: After the final video is ready, the next step is promotions and advertisements! The recorded videos can be repurposed into shorter video snippets and highlights for promotion and advertisements. These highlights can include key pointers of the video – such as moderators highlighting quotes or messages, key moments of the event or the crucial learnings from the video. Machine learning here can detect and highlight such moments with the help of cues such as applause or laughter by the audience or keywords inserted. This reduces the editor’s work and accelerates the video production process by isolating the clips and integrating them to form a highlight reel. 

Lastly, we can surely say that video creation will become fast and cost-effective with the integration of machine learning. Whether you are a technician or a moderator, or just a viewer – the integration of machine learning with video creation enhances the experience of making and viewing the video on every platform. Through machine learning, the video creation can be streamlined, automated and, more importantly, personalised as per the needs and requirements of the user for recording and live streaming.