Constructs of Natural Language Processing
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The World Wide Web (WWW), a rich source of information, is growing at an enormous rate with an estimate of more than 29.7 billion pages on the World Wide Web as of February 2007; English is still the dominant language on the web. However, statistics on global internet usage reveal that the number of non-English internet users is steadily on the rise. Making this huge repository of information on the web, which is available in English, accessible to non-English internet users worldwide has become an important challenge in recent times. Thus,The input or output of a natural Language processing s...
The World Wide Web (WWW), a rich source of information, is growing at an enormous rate with an estimate of more than 29.7 billion pages on the World Wide Web as of February 2007; English is still the dominant language on the web. However, statistics on global internet usage reveal that the number of non-English internet users is steadily on the rise. Making this huge repository of information on the web, which is available in English, accessible to non-English internet users worldwide has become an important challenge in recent times. Thus,The input or output of a natural Language processing system can be either written text or speech. To process written text we need to analyze: lexical, syntactic, semantic knowledge about the language, discourse information, real world knowledge to process spoken language, we need to analyze everything required to process written text, along with the challenges of speech recognition and speech synthesis. It focus a new model of MT system in which Rule-Based, Dictionary-Based approaches are applied for English-to-Kannada/Telugu Language Identification and MT.
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