The Rise of AI in Linguistics: From Chatbots to Language Translation
The unparalleled developments in the field of artificial intelligence have marked it as transformative technology with the potential to change the fate of how we operate in the world. Given that the field of linguistics has led the charge in the development of AI by helping it parse natural language, AI too, now that it is developed, has begun to exert a mutually reciprocal transformative role on the field of linguistics. AI-integration has overturned how we communicate and interact using language.
Let us take the example of chatbots. Chatbots have emerged as one of the most important forms of AI-powered interface, and have changed the way customer service and support functions. Chatbots are an example of conversational AI, which refers to the machine’s ability to interact with humans through language. New age chatbots have evolved to offer convenient, fast-tracked and personalized experiences from companies. Latest chatbots are able to execute a wide range of tasks to expedite customer experience that involves automatically resolving requests and providing solutions to customer problems.
This has had a significant impact on linguistics too. Powered with next-generation AI models, chatbots can help in the following areas in the field of linguistics:
Sentiment Analysis: A mix of natural-language processing, computational linguistics and machine learning techniques have enabled chatbots to gain the ability to process and analyze human sentiment or emotion, even if they do not actually understand it. This allows them to detect how an individual is feeling at a specific point from the tone of their language.
Language Translation: The translation facilitated by AI is a machine translation process that relies on complicated deep learning algorithms. This allows AI to make use of what we would call as intelligent behavior to understand a source text using reason and generate it into a target language. This ability is predicated on AI being able to analyze large amounts of text data in multiple languages to understand the relationship between words, phrases, and meanings.
Generative AI: Advancements in machine learning, such as transformer neural networks, have allowed the creation of generative AI. Generative AI lets developers train codes to understand natural language in a way that allows it to create original creative texts such as poems, song lyrics, short stories, and essays, in a way that it closely resembles human speech. The best example of this is of course ChatGPT.
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