As a part of Software AI, NLP (Natural Language Processing) assign machines with human-like abilities such as understanding written text and spoken words. NLP is a branch of computational science, which combines Computational Linguistics with Machine Learning (ML), Deep Learning, and statistical models. With this combination, machines become so powerful that they fully understand human language with the intent and feeling expressed in utterances.
NLP in Chatbots
In technologically advanced workplaces today, several companies are opting for chatbots to automate and streamline various tasks.
An artificially intelligent system with capabilities of NLP and ML help machines understand what users are saying and learning it without any human intervention.
These two technologies have made it possible to initiate a conversation between a bot and a human.
Features of AI Chatbots
Following are few applications of NLP Chatbots that can improve their functioning to serve various business operations best:
- Speech Recognition
- Named Entity Recognition (NER)
- Intent Classification
- Sentiment Analysis
Importance of NLP (Natural Language Processing)
Applications of NLP are directly linked to language as it involves machine processing of human languages, like English, Spanish, French, etc. Following applications of NLP mark their undoubted importance:
NLP, with its speech recognition capabilities, can convert spoken speech into written speech. This technology is applicable in systems that receives voice commands and responds in audio format.
Automatic Text Summarization
NLP enables automatic text summarization. It is used to extract the most important information from larger texts like legal documentation or scientific articles.
Text summarization is carried out in the following two types:
- Extraction-based Summarization: As the name suggests, the system extracts the most relevant sentences from the text and provides a text summary.
- Abstraction-based Summarization: This is the most common type in which the system paraphrases the most relevant information from the text.
Named Entity Recognition (NER)
This keyword extraction technique extracts words belonging to a category type such as names, figures or places, etc. It enables the recognition and categorization of specific words.
Recognizing the implicit intentions
Enabled with the power of NLP, machines cannot just recognize words of a specific category, but they can also recognize the implicit intentions in sentences.
For instance, with the statement “If these jeans weren’t this tight….” with just this statement, the system can identify what the user really meant: “If these jeans weren’t this tight, I would buy it.”
This particular feature of NLP can help you detect potential customers through your business’s social accounts, email, or chatbot.
Another important application of NLP is its ability of text correction. Such programming helps writers and editors while writing, or revising text.
It enables the correction in spelling and grammar. It further suggests the rephrasing of such sentences.
A system can translate one natural language into another with the help of linguistic knowledge of several languages. It provides fluent speech in the output language by retaining the meaning of the input language.
For Example, Google Translate.
Machine translations are crucial in the diverse and inclusive world we live in.
While machines are yet to understand certain sentiments like irony or sarcasm, they can identify if sentiment is positive or negative through some clues.
NLP chatbots have reimagined the way we do businesses. Machines are recognizing human sentiments and responding accordingly only to ensure improved customer services. While implications of NLP chatbots are inviting machine-human conflict by putting forward potential unemployment concerns, this technology is not going to relinquish any soon. Meanwhile, you can foster your business with the optimal adaptation of this technology.