NLP i.e. Natural Language Processing is a field of computer science that deals with human languages and computers. Natural Language means languages that humans speak – English, Hindi, Japanese, Marathi etc, whereas artificial languages are C++, Java, PHP etc.
As computers evolved, humans were made to “speak” to computers in that language that computers understood. NLP is exactly opposite and hence is very complex. Human speech is not always precise and accurate and also keeps on changing (e.g. slang words). Humans are trying to program computers to learn and understand human languages. This field deals with the problems and providing solutions in this field.
Why NLP is important?
With the progress made in Artificial Intelligence, it is becoming important that machines understand and learn human languages. This will make interaction between humans and machines very productive. Also, it will help in taking the AI to masses and bring benefits to the human kind. NLP forms the core of progress in this direction.
NLP has several areas which are very complex, yet good progress has been made in those areas.
- Speech to text
- Understand the language and translate it correctly into text.
- Optical Character Recognition
- Identify written characters and convert them in computer understandable format to process further.
- Question and Answers
- Program machines to understand Questions and provide accurate answers which humans can understand.
- Sentiment Analysis
- Process large data and understand the emotions expressed in that data
- Machine Translation
- Automatically convert text from one human language to other human language
General History of NLP dates back to 1950. Since then various research and development has resulted into various algorithms which are helping machine learn faster and better. With advent of Cloud, innovations in NLP has resulted into several APIs available for NLP:
- IBM Watson
- Amazon Lex
- Google Cloud Natural Language API
- More
Reference Links:
Related Keywords:
Automatic Speech Recognition, Speech to Text, Machine Learning, Sentiment Analysis
Application Areas:
Search Engines, Fraud Detection, Sentiment Analysis, Bio-Medical field, Forensic Science and many more
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