Natural language processing is a subdivision of AI (artificial intelligence). It is mainly associated with the connection between computers and human language. In NLP, machine learning algorithms are applied to written and spoken content. For instance, natural language processing is used to recognize speech, summarize texts and documents, detect spam, and answer questions.
Examples of NLP in our daily life
We can observe these NLP applications in our everyday life. For example, almost every person has a smartphone now. Smartphones have a speech recognition feature available. The smartphone can understand what the user is saying using natural language processing or NLP. In addition, a lot of people use personal computers in the form of laptops that has speech recognition system. Some specific examples of NLP are as follows.
It is the virtual assistant of Microsoft. Cortana can recognize the human voice. People use it to set reminders, send texts and emails, open different applications, track local and international flights, play fun games, track parcels and packages, check weather predictions, etc.
The virtual assistant of Apple Inc.’s iOS, macOS, and watchOS is Siri. Like Cortana, you can perform a number of functions with Siri by voice commands. Such as, you can call a friend, send a text to your employer, send an official email, set timers, take a picture of yourself, start navigation, or even set an alarm.
Paraphrasing tool uses Natural Language Processing (NLP) to quickly and accurately extract key message concepts from the paraphrase. The technology automatically parses and analyzes the source text. It also provides you with suggestions to improve your sentences
Gmail is an email service that is very popular now. It was developed by Google. It is using natural language processing to detect spam. Thus, it filters out spam emails by detecting the text words that indicate spam.
Components of NLP
There are two fundamental components of natural language processing (NLP). These components are
Natural language understating and natural language generation
Natural language understanding (NLU)
Natural language understanding is difficult compared to the natural language generation process. This is due to the ambiguity in a language. For instance, the word “match” can mean a partner and a football match. This is called lexical ambiguity where one word has more than one meaning. It is necessary to interpret the sense of a word correctly to comprehend the sentence. This difficulty is easily overcome by using the technique of parts-of-speech tagging.
The perfect example of NLP is a paraphrasing tool which use NLP technique. In addition, there may be other types of ambiguity such as referential ambiguity and syntactical ambiguity. Due to such confusion, natural language understanding is not an easy task.
Natural language generation (NLG)
NLG is the process in which proper sentences and phrases are generated in the form of natural language. Natural language generation comprises text planning, sentence planning, and text realization. During text planning, the system retrieves relevant content from the database. In sentence planning, it chooses appropriate words, forms meaningful sentences with a specific tone. Text realization means mapping the sentence plan into a sentence structure.
Open-source libraries of natural language processing
The open-source libraries of NLP make the algorithmic blocks of natural language processing available for practical applications.
- Apache OpenNLP: It is an ML (machine learning) toolkit. It provides tokenizers, part of speech tagging, conference resolution, etc.
- NLTL (natural language toolkit): It is a library of Python. It provides modules for text processing, tagging, stemming, etc.
- Stanford NLP: It is a suite of natural language processing (NLP) tools. It also provides the same services.
- MALLET: It is a Java package.
Natural Language Processing and content creation
There are several NLP paraphrasing tools available free of charge. These tools have truly transformed the field of content creation. Because with these tools, it is conceivable to create new and unique content. Now, content creation is not limited to humans only. Natural language processing-based tools use the available data and create new content from it. In this way, it is now possible to create much more content in a short period of time. In addition, NLP-based tools can summarize long texts too. These tools recognize different parts of a piece of content. They ignore the parts that are not important while keeping the essential points.
How NLP modules has transformed content creation?
As mentioned earlier, NLP is now a common part of our daily lives. It is a game-changer in our everyday life. NLP modules have also transformed the field of content creation in the following ways.
By generating precise content
The NLP-based content creation tools have the ability to create accurate data. This data is comprehensible to human beings. Such tools give results that are even better than humans.
No grammatical errors
The NLP-based tools produce error-free content. As writing error-free content is an important goal of academic and blogs writing, these tools are giving tough competition to writers and bloggers.
No spelling mistakes
Along with creating grammatically correct content, NLP-based writing tools create content that has no spelling mistakes.
Content creation takes a lot of time when humans do it. However, natural language processing can accomplish such a complex job within a few moments.
Create content anywhere
Humans can create content only when they are in a certain peaceful environment. They require a relaxed mind to do this creative work. On the other hand, the NLP-based tool can create content anywhere. Only an electronic device with an internet connection is required to do the job.
A lot of free NLP based tools
Due to the availability of many free NLP-based paraphrasing tool, it is now much easier to get unique content. Anyone can use these tools without spending any money.
NLP is now a part of our lives and we carry it with us in the form of our smartphones and laptops. The goal of NLP is to assist human beings in many minor but important tasks. Natural language processing has also transformed the field of content creation.
Now, content creation is not restricted to human intellect only. Natural language process or NLP based tools and libraries have transformed content creation by the generation of accurate, error-free content in a short time. The free-of-charge NLP tools are playing their roles in this transformation.