Natural Language Processing (NLP)
Natural Language Processing enables computers to understand, interpret, and generate human language. NLP powers chatbots, sentiment analysis, translation services, and voice assistants. For India — wi…
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Definition
Natural Language Processing enables computers to understand, interpret, and generate human language. NLP powers chatbots, sentiment analysis, translation services, and voice assistants. For India — with 22 official languages and hundreds of dialects — multilingual NLP is particularly critical for building inclusive digital products.
Key Points
- Sub-tasks include tokenisation, named entity recognition, sentiment analysis, and machine translation
- Transformer architecture (BERT, GPT) revolutionised NLP performance
- Indian NLP challenges: code-switching, multilingual content, limited training data for regional languages
- Applications: customer service bots, document processing, content moderation
Frequently Asked Questions
Indian businesses use NLP for multilingual customer support chatbots (handling Hindi + English code-switching), sentiment analysis of social media mentions, automated document processing (KYC, invoices), and voice-based interfaces for users less comfortable with typing.
Yes, though with varying accuracy. Hindi, Tamil, Bengali, and Telugu have reasonable NLP support through models like IndicBERT and AI4Bharat's IndicTrans. Smaller languages have less training data, but Sparks AI uses transfer learning and data augmentation to build effective multilingual models.
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