Challenges of Implementing Natural Language Processing

As text and voice-based data, as well as their practical applications, vary widely, NLP needs to include several different techniques for interpreting human native language. These could range from statistical and machine learning methods to rules-based and algorithmic. NLP has immense potential in real-life application areas such as understanding complete sentences and finding synonyms of matching words, speech recognition, speech translation and writing complete, grammatically correct sentences, and this need has now become amplified.

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