“01001000 01100101 01101100 01101100 01101111 00001010”

Did you get that? For those who didn’t read the above binary,the direct translation is “Hello”.

Don’t be ashamed that you can’t read the above binary.Because we can’t understand the computer language and computers have difficulty in understanding our human language too.When you think about the variability of the spoken words,there must be a lot of languages,dialects,mispronunciations and more.

Let’s start to know about Natural Language Processing(NLP). Some of the technology have a magical technique to understand natural language such as Siri,Google assistant etc…,you wonder how it is possible to achieve so complex.You start searching to know about this magical technique but you didn’t get the clear idea.

Well, the ultimate goal of this blog post is to give the quality overview of the NLP for those who want to know about it and get innovative ideas in emerging technology.

What is Natural Language Processing ?

AI & Medical Insights: Get in the Know — Kernel

Artificial intelligence(AI) has become part of our lives over a period of time.

Natural language processing is not science,it is a computer science.It’s focuses on interaction between computer and human language. NLP is the interdisciplinary field of computer science and linguistics,using machine language to achieve the goal. NLP is the ability for computers to understand the human language.It is a subfield of artificial intelligence.

Syntactic analysis and Semantic analysis are the main techniques used in the NLP tasks.It allows the machine to find the difficult meaning of the sentences. NLP mostly rely on machine learning to get correct meaning from human language. Machine language and Deep learning are not NLP.They are used to solve complex problems not related to NLP.

Think about the communication loop between the two people:a sender encodes a message through the medium(spoken or in written form) and the receiver decodes the message and responds to the sender.The same communication loop in the computer has lot of gray area in the encoding and decoding of the message.

Read this blog post to know about the difficulties and solutions of various NLP related problems.

Why is NLP so difficult ?

Some words in english have the same synonyms and the same pronunciation.And a single spelling of the word can have multiple meanings and two words can sound alike but have different meanings.

Homonyms – Two or more words that have the same pronunciation but have different synonyms can be problematic for the system because they aren’t written in the text form.Full sentences contain a noun,verb,part of speech ,adverb, adjective, conjunction and more.Phrases and sentences also complicate computers to understand the human language.

Ambiguity is also a major problem in natural language because it has more than one meaning of the word.Basically it increases the range of possible interpretations of natural language.

Human Cognition uses inbuilt socio culture context and knowledge about the world to learn the language.Mother tongue is the language which we develop using our socio culture context and with the context which we develop by this is utilised in learning order.To make proper sense of what we are talking we make use of knowledge about the world in phrasing the sentences. These make the natural language more complex.Humans have a firm grasp on the context of each word being used.

5 General Steps in NLP :

Natural Language Processing Step by Step Guide | NLP for Data Scientists

Lexical Analysis :

It identifies and analyze the structure of words. Lexicon of the language means the collection of words and collection of phrases in a language. Lexical analysis is dividing the whole chunk of text into paragraphs, sentences and words etc…

Semantic Analysis :

Mapping syntactic structures is done by Semantic analysis and the object in the task domain.It draws the exact meaning from the text and the text is checked for meaning.

Syntactic Analysis :

It involves, analysis of words in the sentences for grammar and arranging the words in the manner that shows the relationship among the words.

Discourse Integration :

The meaning of any sentences depends on the meaning of the sentence just before it. And Brings the meaning of immediately succeeding sentences.

Pragmatic Analysis :

It is re-interpreted during this analysis.It involves deriving those aspects of language which require real world knowledge.

Speech Recognition :

Speech is the most efficient and natural way of communicating the information among humans.If we recognise the speech in technologies, it will be more profitable. The process of recognizing the human speech is known as speech recognition.If you ask siri or google assistant,any questions,it will refers to the millions of audio files that have been tagged to give the results to the speaker who asked questions. But first, computer must understand the difference between vowels and consonants and the computer microphones should have a clear magnitude of the frequencies to know what the speaker is asking. As a lightwaves, Soundwaves resonate in a microphone from the vocal tract is known as “formants”.

How Speech Recognition Works :

First, Voice acoustics are picked up by a microphone. Then Waveforms vibrate the microphone’s diaphragm which measures amplitude of the voice.

How to Build Domain Specific Automatic Speech Recognition Models on GPUs |  NVIDIA Technical Blog

The Fast Fourier Transform algorithm converts the amplitude to the formats and frequency. And Finally the speech is converted into the text to be further analysis using NLP.

How NLP is used today ?

Natural language processing is used in many different ways in technologies.From the asking about the weather frosting to analysis of social media harassment.You will have interfaced with NLP, When you asking questions to siri or google assistant. The most difficult Use Case is sentimental analysis. Analyze the full context is also a complex task to the system.

Natural Language Processing and its use cases

NLP can be used in Spam detection, Parts of speech recognition, Sentimental analysis, Text composition,Question answering, Automatic summarization and conventional interface etc…

Final Thoughts :

NLP is a vast field and young field in Artificial Intelligence. Natural language Processing plays an important role in supporting machine- human interaction in the real world.I hope this blog post will help you to know more about NLP.