Putting the Context in Your Content
We produce, collect, aggregate, and adapt enormous volumes of data on a daily basis. When it comes to all of this content, how do we determine context? To solve this issue, we need to automate the extraction of contextual information from Big Data.
With video content in particular, even speech-to-text automation leaves behind errors and large gaps in the information such as which words to capitalize. Content owners spend countless hours and budget resources transcribing and correcting this messy data.
aioTV is using Natural Language Processing to give content owners the ability to automate the process to produce contextual, quality metadata regardless of the velocity and variety of raw data.
What is Natural Language Processing (NLP)?
A form of Artificial Intelligence (AI), NLP is a way of modeling language in a way that computers can understand it and make use of it. It does this through:
- Tokenization (Turning words into meaningful units)
- Tagging (Understanding the meaning of words in terms of parts of speech)
- Parsing (Determining syntax by understanding the relationship between words)
- Entity Recognition (Understanding what each word refers to such as a person, location, weather event, temperature, year, etc.)
What is the difference between Machine Learning and NLP?
Machine Learning is also a form of AI, but compared to NLP, it requires quality data to produce meaningful results. Once NLP has finished feature extraction, Machine Learning empowers software to generate even more useful metadata such as tags and topics. It also classifies and categorizes the data. NLP can then come back into play to add context to the machine learned data.
What is the key benefit of using NLP?
When it comes to automating data creation, many people believe Machine Learning is the only solution. However, NLP is the key to putting context back into the extracted data. NLP can do this by turning raw data outputs from machine learning into quality, human-readable information.
What can NLP be used for?
NLP can be used for automating the transcription, annotation, and metadata generation from any video content including weather, sports, culinary, news, etc.
How does aioTV use NLP to ‘generate’ metadata?
aioTV’s MetaGenerator is a solution designed to harvest quality metadata from video content. Using industrial strength Machine Learning and Natural Language Processing, MetaGenerator transforms messy data into human-readable captions. Users can then easily archive, search and discover video with accurate descriptive metadata such as description, context, title, keywords, tags, categories, and topics.
Caption: Rhode Island now these areas are bracing for a cool down big cool down but also more rain some more rainbows could be seen as we head toward sunset fifty five in New York City right now we're not going to be moving too much we're talking about fifteen twenty degrees below average for portions of the northeast it's humid outside there's a lot of rain around moving in towards New York City and also to the upstate in New England Title: Rain in Rhode Island and New York Description: Cool and Rain in Rhode Island. Rain in New York City. Tags: Cool, Rain, Rhode Island, New York, New England
Content owners now have the choice to continue to spend time and money on quality metadata, or automate the process and use contextual data to focus on revenue opportunities. For more information on MetaGenerator, visit aio.tv/MetaGenerator