Natural language processing, Language The Power of Natural Language Processing | How It Works | Real Life Examples
Talk, natural language processing is a technology that focuses on the interaction between computers and human language. It allows machines to fetch information from text or speech and offer insights and intelligence to humans. So, to put it in simple words, natural language processing is the ability of a computer program to interpret human language through text or speech known as natural language and its also a subset of artificial intelligence. Natural language processing has been around for at least 50 years and has firm roots in the linguistic sector. It has a lot of real world applications in various fields, including business intelligence, medical research and search engines. Natural language processing can handle and analyze large volumes of text data without fatigue and bias. It can also structure highly unstructured data sources. Natural language processing is important because it helps resolve ambiguity in language and adds useful information on top of it. Its contribution to text recognition and analytics is unprecedented. Some other applications of natural language processing include sentimental analysis, chatbots and virtual assistants speech recognition such as siri and machine translation like google translate. Sentimental analysis is commonly used in social media platforms and the result can show peoples attitude toward a topic. A chatbot is commonly used in the service industry, saving both agents and customers. A lot of time and speech, recognition and machine translation can be found in smart devices. These functions are designed to make peoples lives, more convenient and efficient, and in todays, video were going to walk through how natural language processing works and some of its real world applications.
As always, if you find this topic interesting, then you can. Let us know by hitting that, like button and subscribing to this channel for more videos, you can also let us know if you find it interesting by leaving a comment in the comment section down below now: lets jump into it Music. So how does natural language processing work, natural language processing, allows a computer program to understand and interpret natural language as humans do, irrespective of the language being spoken or written natural language processing leverages the potential of ai to take real world input process it and interpret it In a way, a computer can understand just like how humans have sensors, including eyes to see and ears to hear computers have programs to read and microphones to capture sound. A computer also uses a program to process the respective inputs just like how humans use their brains to process information during processing. The input is converted to code that is understandable by the computer. Now there are two main phases of natural language processing, theres data, pre processing and algorithm development. Now data pre processing includes preparing and sorting text data for computers to be able to understand and examine it. Pre processing puts data in an understandable form and pinpoints features in the text that an algorithm can work with, and there are a lot of ways that this can be done, which includes stop word, removal stop word. Removal is when common words are removed from text so dissimilar words that offer the most insight about the text.
Stay, lemmatization and stemming lemmetization and stemming is when words are lowered into their root forms to process. Tokenization tokenization is when text is broken down into smaller words. To process and part of speech tagging part of speech tagging is when words are marked on the basis of the part of speech that they are, for example, adjectives nouns and verbs once the data has been pre processed. It starts processing with the help of an algorithm thats developed right after the pre processing, and there are a lot of natural language processing algorithms, so were going to look at two of the most commonly used first theres, the rules based system. Now this system follows carefully designed linguistic rules. This is an approach thats used in the early stages of natural language processing and is still used, and second theres, a machine learning based system, machine learning, algorithms, leverage, statistical methods to perform tasks based on training data that theyre inputted and adjust their techniques as more data Is processed through a combination of machine learning, deep learning and neural networks, natural language processing, algorithms make their own rules by means of frequent processing and learning. Now lets have a look at three real world applications of natural language processing, voice, assistants, im sure, youve heard of google assistant apple siri and amazons alexa. All of them are voice assistants, voice assistants are software programs that leverage the power of speech, recognition, natural language, understanding and natural language processing to analyze the verbal commands of a user and perform actions, as required now im sure a lot of us cant.
Imagine our lives without our voice assistants. Now, over the years, theyve transformed into a very reliable employment companion from finding a restaurant to booking a flight ticket. These voice assistants can do so much chat, bots customer service and experience are some of the most important aspects of a business. It can help a business organization, improve their products and work in increasing their customer. Satisfaction by interacting with every customer manually and solving their issues can be a time consuming and costly task. This is where chat bots really come in handy. They help businesses in achieving the goal of a successful customer experience. Currently, a lot of businesses use chat, bots for their applications and websites which helps to resolve basic customer queries. It not only simplifies the process, but also saves customers from the frustration of waiting to talk to customer representatives. Besides, it can eliminate the cost of hiring a customer service representative for the organization. Initially, chatbots were only used for solving the problems of customers, but today, theyre also known as personal companions from recommending a product for shopping to getting customer feedback. They can do so much more. Three is social media monitoring more and more people. These days have started actively using social media for things like posting pictures and thoughts about specific products or policies. These could include critical information about a persons likes and dislikes so examining this unstructured data can help in deriving valuable insights, and this is where natural language processing comes into the picture.
Currently, different natural language processing techniques are used by businesses to study social media posts and know what customers think about their products. Businesses are also using social media monitoring to solve issues that their customers are experiencing related to the products. Natural language processing is one of the most opportunistic fields within ai and its already present in a lot of applications that we use on a regular basis from chat bots to voice assistants. Thanks to natural language. Processing businesses are automating some of their day to day processes and making the best use of their unorganized data, getting valuable insights that they can use to improve customer satisfaction and deliver successful customer services. So there we have it once again. If you enjoyed this video or found it interesting or helpful, then dont forget to let us know by hitting that, like button and subscribing to this channel for more videos.