Today’s computer language technology is birthing a better future of technology that would communicate with humans using human language more effectively.
Natural Language Processing is the field of artificial intelligence through which this can be achieved.
What Is Natural Language Processing (NLP)?
NLP is an artificial intelligence and machine learning integrated feature that uses computer algorithms to aid computers in analyzing human language and then understanding and recognizing both text and spoken words in its processing.
The drive of NLP is to reach a level in the computer world where we can efficiently interact with computers without using any programming or artificial language.
Just as a pupil is taught to understand word relationships in English language, NLP helps computers do the same by analyzing input such as text or speech; it breaks a sentence into separate parts and matches them to a solid database of past experiences of word semantics and syntax.
Steps Involved In NLP
- The computer converts vocal inputs (speech commands) to text. It is called the speech-to-text process.
- The part-of-speech (POS) identification or word-category disambiguation defines words according to the part of speech they belong to, and also maintain the distinctive use of the word in the sentence.
- The third stage converts back its most suitable response to a written or audible format.
The NLP can also understand that words can have different contextual meanings in a sentence depending on the use, whether in the form of idioms, sarcasm or grammar.
See the illustration below;
I am done reading the book on programming.
TimCollins should book a sitting space at the tech event in February.
The government must book lawbreakers in the tech space.
In each sentence, the word ‘book’ has a distinct meaning, so the NLP enables computers to understand word complexity when taught how to go over high grammatical statements.
Natural Language Processing finds applications in digital assistants, voice-operated systems, customer service chatbots, text prediction, speech-to-text dictionary software, spam detection, Google Translate, social media content analysis and name entity recognition.
But the expectation is to have a computer that can interact more using human language.
Tone and inflection of speech which differ from accents, word ambiguity and the continual use of borrowed words, can be a challenge with NLP technology. However, is it possible to get an NLP technology tailor-made for every accent in the world?
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