A great introduction to natural language processing!
What is Natural Language Processing?
Natural Language Processing (NLP) is a field of artificial intelligence in which computers understand, analyze, and get meaning from human language in a beneficial and excellent way. By making use of NLP, developers can create structure and knowledge to perform tasks like translation, automatic summarization, relationship extraction, named entity recognition, and topic segmentation.
NLP is used to find text thereby allowing machines to recognize how humans speak. This human-computer interaction allows real-world applications like sentiment analysis, automatic text summarization, named entity recognition, parts-of-speech tagging, and more.
Importance of Natural Language Processing:
The biggest advantage of NLP for businesses is the ability of technology to identify and process great volumes of data including online reviews, news reports, social media platforms, and others.
Moreover, by analysing and collecting business data, NLP should be able to produce business value insights into great performance. In addition, NLP models can detect any existing issues and take appropriate mitigation measures to enhance performance.
Google speech to text will be able to accomplish all of this by training machines to understand human language in an accurate, faster, and consistent way than human agents.
The technology is able to consistently process and monitor data. This helps brands update with their presence online and not get pierced with inconsistencies.
Uses of Natural Language Processing For Business:
1. Speech recognition:
Many of you would have wondered while talking to your voice assistant or Google assistant about how you recognize your voice and the ways of word interpretation and the appropriate responses of it. This is mainly due to the recognition of speech.
This recognition is a technology that enables the computer to convert voice input data into a machine-readable format. There are a lot of fields where speech recognition is used like adding speech to text, virtual assistants, sending emails, and translating speech. It is used in search engines where the users can say the names of their search requirements and get the required results thereby making your work more convenient than typing out the entire command.
2. Chatbots and voice assistants:
All of you would have been well versed with the ideas of voice assistants and chatbots that are combined in many websites to help and guide new users. Voice assistant is a software that uses speech recognition and NLP to understand the voice commands of users and perform accordingly. Similarly, these chatbots are programs that are designed to assist a user and answer any query that he/she might have.
Most virtual assistants and chatbots have pre-programmed answering systems that follow specific patterns and rules while answering. Excellent AI has enabled certain voice assistants to interact with users and respond appropriately.
3. Auto prediction and auto-correction:
There are several software available nowadays that check the spelling and grammar of the text that is being typed and save people from humiliating grammatical and spelling mistakes in the text, emails, or other documents. NLP plays a pivotal role in those functions and software.
This is one of the most commonly used applications of NLP. This software offers several features like correcting grammar, suggesting synonyms, giving clarity to the document, rephrasing sentences, and can even predict the tone of a sentence that might be implied by the user.
Auto prediction is also a characterization developed through NLP where the laptop or computer suggests automatic prediction of the text which is being started to type. This saves a lot of time for users and makes the job easier for them.
4. Email filtering:
Most of the professional work is carried out through emails and it would be quite a big problem if all emails received are not segregated into different sections. Gmail categorises all the emails into social, primary, and promotional sections. Even all the emails are spammed into a different section so that they don’t make the inbox to be full.
This is done with the assistance of text classification which is a technique of NLP. It would certainly help in saving time and does not miss any significant email that might have gotten lost if all the unwanted emails get accumulated in the inbox.
5. Sentiment analysis:
Human speech could be quite difficult to interpret as it involves sentiments and expressions beyond wanted meanings. Expressions like a threat, sarcasm, exclamation, angriness, etc. are very hard for computers to be identified by the computer.
The machine will be able to catch on to various sentiments that might be suggested through the user’s command with the assistance of Natural Language Understanding (NLU) which is the subfield of Natural Language Processing (NLP).
Through using this you can analyze customer reactions and handle social media disputes easily by reducing negative comments as much as possible.
6. Marketing Target Audiences:
If you had ever searched for any objects or products on any shopping sites, you would have often seen ads of those products and the other related ones on the other sites. This type of advertising is done with the help of NLP and is known as targeted advertising.
This can be highly advantageous to several companies and saves a lot of investment as the ads are only shown to customers who are actually fascinated by the product which is identified on the basis of the online activity.
Social media has put the whole world together but with unity comes hardships like the language barrier. This hurdle has been easily overcome with various translating software that works individually or is combined within other applications.
This process is known as Machine Translation which uses Natural Language Processing and has made a lot of enhancements in the field due to the availability of huge amounts of powerful machines and data and improvement in the field of neural networking and Machine learning.
It has specifically helped social media users who are connected to people across the world or in grabbing foreign customers. Platforms like Instagram and Facebook have their own translation software combined within the main application.
Thus, Natural Language Processing is used in several fields today and has made communication efficiently with devices easier.