With the rising chatter around regional microblogging site Koo, we decided to shift the spotlight focus on this platform and why this is an opportunity to strengthen NLP capabilities for local languages.
What is Koo?
Koo has some similarities to the world-renowned microblogging platform Twitter where users can express their opinions, share news updates and speak about trending topics.
One of the prominent differentiators for Koo is that the indigenous app offers services in various local languages allowing many Indians to use the platform with ease. With a population of over 1.3 billion people where a vast majority still converses in their regional language, the platform is trying to provide an immersive language experience to its users.
A quick look at its features
It allows users to follow individuals and browse through a feed. Users can write messages in text or share them in audio or video formats. It has Kannada, Tamil, Telugu, Tamil, and English language options, with others coming soon. It also allows people to express their opinions in their local languages.
Messages can be written up to 400 characters and are called “Koo”. There are language communities that essentially show all content in a particular language. One can converse on the platform in regional languages namely Hindi, Kannada, Telugu, Tamil Marathi, Bengali, Malayalam, Oriya, Punjabi, Assamese, and Gujarati.
Understanding a language means knowing words, phrases, syntactic forms, and concepts and also knowing how to link those concepts together in a meaningful way. This requires extensive knowledge about the languages and the ability to interpret it. NLP certainly provides useful functionalities such as part of speech tagging, lemmatization, phrase extraction, text categorization, entity extraction, topic extraction and parsing
How can it help with strengthening NLP?
An opportunity to diversify the nature of speech and expression through the emphasis on regional languages
This can help fortify NLP capabilities and aggregate datasets in different languages
Increased emphasis on providing NLP algorithms with large collections of text with all possible permutations and combinations
Heralding a new era of software development that is more suited to a niche audience
NLP is defined as the automatic manipulation of natural language, like speech and text, by software. Computational linguistics also became known by the name of natural language process, or NLP, to reflect the more engineer-based or empirical approach of the statistical methods. NLP is tricky and tough to crack since it is messy. Hence, it is vital to have such platforms that can take a shot at solidifying NLP at a regional language level, thus showcasing the strength and impact of technology on a macro as well as micro-level.
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