NLP (Natural Language Processing) is an area of artificial intelligence and computer science which investigates how computers interact with human languages by devising algorithms and models which recognize, comprehend and generate human lingual structures.
Natural Language Processing: Natural Language Processing encompasses several important tasks. Speech recognition allows computers to understand spoken languages; comprehension refers to reading materials written in natural languages, while generation uses computer algorithms similar to what a person might produce using paper and words written on it.
Natural Language Processing: Applications
NLP can be applied in many fields, from translation and language synthesis, text-to-speech synthesis and sentiment analysis, through to entity recognitions. Also utilized by virtual assistants and chatbots alike.
Natural LanguageProcessing: Deep learning, particularly the use of neural networks, has driven recent advancements in NLP. Tasks such as sentiment analysis and machine translation have seen vast improvements due to these models due to improvements in computer resources, large training data sets, and other factors.
Natural Language Processing: Challenges
NLP still faces numerous hurdles to adoption, such as managing ambiguity and context, understanding idiomatic expressions or sarcasm, handling different languages or dialects and comprehending text as humans do. Furthermore, Natural Language Processing algorithms still struggle with reading in an intuitive fashion similar to humans do so.
Conclusion
Natural Language Processing is an ever evolving fields with varied applications. As deep learning techniques evolve and more data is accessible, we should anticipate an increase in accuracy and capabilities among NLP systems in the near future.
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