Artificial Intelligence (AI) solutions are progressively used in software services. To capitalize on this game-changing technology, companies must determine how to optimize their use of AI in order to unlock its full potential.
In this article, you'll learn all about the different AI technologies that video editing companies should consider upgrading to.
A very important and essential AI technology that you should consider implementing is Speech-to-Text. Also known as speech recognition, Speech-to-Text converts audio into written text while preserving its meaning, making it a reliable and efficient tool. This can be particularly useful in the video editing process as it enables the machine to first transcribe the audio, and gives you the flexibility to make necessary modifications later.
Moreover, most people who watch videos online do so without any audio whatsoever. By using AI software to add accurate and polished subtitles, your video/audio editing company can expand its audience and enhance its value proposition.
Plus, instead of having one engine that generates subtitles for your users' videos, you can have several ones to choose the best transcription. This will allow you to make your users' tasks easier and increase their satisfaction by offering them the most optimal transcription for their needs.
Text detection can recognize and identify text within the video, providing a better understanding of the content. This can help to automatically categorize and tag videos based on the text detected. It can also be used to generate searchable text from the video, which can help users find specific sections of the video more easily.
Text recognition can be used in video surveillance to automatically recognize license plates, faces, and other text in the video stream, which can help identify suspects and vehicles involved in crimes. Another great way to use text recognition would be in interactive educational videos to allow students to interact with the content on a deeper level. For example, students could click on words to see definitions or translations.
Another technology to consider implementing to your video editing software is machine translation. Also known as automated translation, it is a process in which AI software is used to translate text from one language to another. This feature can be highly beneficial for your video editing company, as it allows you to cater to a wider range of clients who need translation services.
The speed of translation offered by AI is one of its biggest advantages, as it provides fast and efficient translations without the need for human intervention. This allows video creators to translate the subtitles of their videos and make any necessary modifications.
You might want to consider incorporating explicit content detection technologies into your software as well. For instance, content moderation allows you to analyze images or videos to determine and filter out inappropriate media such as violence or pornography. The engine compares the content to a defined threshold to determine its explicitness, and also provides an indication of the degree of explicitness in any media.
Object and face detection technologies can provide more detailed information about the video content, such as the number and types of objects and faces in the video, their location, and movement. This can help to create more accurate visualizations, statistics, or reports about the video content.
Face Recognition can be used to automatically identify and isolate objects and faces in a video, making it easier for video editors to perform tasks such as object removal, background replacement, or face blurring. It can also be used to personalize the video content based on the viewer's preferences or behavior. For example, a video platform could recommend videos based on the viewer's favorite actors or content.
Moreover, object and people tracking technologies can be used to automatically track objects and faces in a video, making it easier for video editors to perform tasks such as adding special effects or animations that follow the movement of the objects and faces.
Last but not least, both can be used in security-related applications, such as detecting and tracking people or objects in surveillance videos.
AI can also easily help you detect logos in images and videos. This tool can be useful in marketing analysis (advertising, sponsorship, social media…) to track how often your brand logo appears in videos, where it appears, and for how long. This information can help your company to measure the effectiveness of your advertising campaigns and to make data-driven decisions about future marketing strategies.
Logo detection in videos can also be used to detect unauthorized use of copyrighted material in order to take appropriate legal action.
Overall, integrating AI into your video software can enhance the user experience and provide more accessibility options for viewers.
To implement these technologies, the easiest and most efficient way is to use ready-to-use services available on the market. They are made available in the form of APIs.
However, there are many suppliers on the market. You have access to multiple providers that each offer you the service you need, whether it is speech-to-text, image and video analysis or automated translation. These providers have performances that vary between each other. This particularly depends on your data (language, image quality, etc.).
Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Video Analysis tasks in their cloud-based applications, without having to build their own solutions.
Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Sentiment analysis API, Summarization, Question Answering, Data Anonymization, Speech recognition, and so forth.
We want our users to have access to multiple Video Analysis engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs :
You need to set up a provider API that is requested if and only if the main Video Analysis API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
After the testing phase, you will be able to build a mapping of providers’ performance based on the criteria you have chosen (languages, fields, etc.). Each data that you need to process will then be sent to the best Video Analysis API.
You can choose the cheapest Video Analysis provider that performs well for your data.
This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because Video Analysis APIs will validate and invalidate each other for each piece of data.
You can see Eden AI documentation here.