Natural language processing (NLP) is a sort of artificial intelligence technology that is going to dominate the translation industry and global communication worldwide. Computers and machines don’t really think or process in terms of the languages that humans speak. They can only understand machine code or machine languages, which is not understandable for most humans. It is hard to comprehend how the series of zeros and ones can process information and perform rational actions.
However, since we invented the first computer, programmers have been using machine languages to interact with computers. There are very few people who can actually understand computer languages, commonly referred to as programmers. NLP (Natural Language Processing) plays a vital role in your computer or machine processing of human speech, and it is one of the major technologies influencing businesses and global communication.
In this article, we’ll get deeper into NLP work, its significance, and its impact on digital businesses.
What is Natural Language Processing?
In computer science, NLP uses artificial intelligence technology to process human speech to perform a particular action. There are tons of data in the natural language that a machine has to comprehend within seconds. Natural language processing is a hard task though because every person has their own unique style of writing and talking. To understand human languages, NLP uses machine learning along with semantic analysis. The text or spoken words are processed by the machine considering the sentence structure, grammar, typos, and context to extract the most appropriate meaning. Advanced technology and AI techniques have made it possible for computers to understand natural languages and give immediate responses.
Today, NLP programs have become so smart that they can even detect emotions in human speech through sentiment analysis. Global businesses can use such NLP apps to detect the sentiment of the customers towards their brand on the internet.
How does NLP Work?
NLP is undoubtedly one of the most influential artificial intelligence technologies because of the higher demand for voice interfaces, apps, and chatbots. However, it is very challenging for such systems to comprehend human languages because of their complexities. Here are some logical reasons why natural languages are hard to interpret.
Firstly, the purpose of human languages is to transfer meaning, instead of just sending passive information or data.
Secondly, human language is not just about words, it also involves symbols and categorical signals that add more meaning to the conversations.
Third, everyone has their own unique way of expressing emotions, so we can’t really say what is the right or wrong way of saying things. Categorical symbols in a language add more meaning and depth to the language. There are multiple ways to interpret those signals.
Three Stages of Natural Language Processing (NLP)
For processing human speech, Natural language processing uses AI technology combined with computational linguistics. The following are three stages in the NLP process.
Stage 1: Data Receiving
In the first stage, NLP has to comprehend the natural language data received. The computer uses a statistical model to recognize natural speech and transform it into a programming language. For this, it splits the natural language speech into small units. Then your computer compares the recent unit with a previous unit of speech.
The output is received in the text format that contains the sentences more likely said. So, this step is known as the speech-to-text process, because in this process the speech is converted into a textual document.
Stage 2: Part-of-Speech Tagging
The second stage of language processing is known as part-of-speech tagging. In this process, the grammatical form of each word is identified, such as verb, noun, future tense, and adjective. The word category disambiguation is done through lexicon rules. Understanding the grammatical form of each word written on the textual document makes it even easier for the computer to comprehend the meaning of speech.
Stage 3: Text-to-Speech Conversion
The third stage of NLP is known as text-to-speech conversion, in which the result obtained from the first two processes is converted into the audible format. For example, when you ask Alexa to set the alarm at 7 a.m. tomorrow, it will scan your location and clock to set your alarm. Similarly, online Chatbots also use this technology to answer the queries of customers and provide them with the most appropriate answers.
Significance of Natural Language Processing
1. Better Customer Support
Today, almost every online brand uses chatbots and customer support applications to provide timely responses to their customers. In this application and chatbots, businesses use NLP technology to make online human conversions. These are AI tools with powerful Natural language processing algorithms that make it possible for such machines to have a conversation with humans. There is no need to hire any human customer support because these machines can give the quickest response to your customers’ queries 24/7.
Rather than sending automated and predefined answers to your customers, these chatbots can have a real-time conversion with customers. There are many chatbots that also offer advanced customer support, including booking a ticket, providing guidelines, and helping customers find the right product or service.
2. Improve Customer Satisfaction
NLP technology is playing a major role in enhancing the online customer experience. Online portals and websites have become advanced enough to respond to customers’ voice commands. Advanced Natural language processing systems give quick responses to customers’ speech and perform relative actions. Some of the NLP tools are not just able to recognize the speech and intent of customers but they can also detect their sentiments. Understanding the sentiments of customers allows businesses to continuously improve their customer services and meet their expectations of customers. It also leads to higher customer satisfaction of their overall experience with a brand. Many brands use such NLP tools to know how happy their customers are and what is making them more satisfied.
3. Higher Conversion Rates
For the marketing executives of companies, enhancing the business revenue is the most critical and challenging job. Businesses use many strategies and tactics to engage potential audiences and convert them into customers. NLP models are also very effective at optimizing the conversion rates that not only improve the business revenue but also reduce the customer acquisition cost.
Businesses use NLP chatbots, applications, and search features to enhance the online customer experience. It keeps the customers engaged with the brand and develops trust and a positive reputation in the market.
4. Save Time and Money
At the end of the day, businesses have to make good profits. To optimize their revenues, businesses must look for a way to cut down the expenses. With it comes to reducing costs, NLP proved highly effective because it saves time and money by improving business processes. For instance, the chatbot is the most effective example when it comes to making customer support less time-consuming and expensive. The research has stated that implementing chatbots can reduce the company’s customer support expense by 30 percent. It reduces the need to hire professional customer support personnel. This way chatbots not only save your time but also cut down the customer support expenses.
It also reduces the workload on employees, and they can focus on more creative tasks that are directly linked with generating more leads and sales.
5. Maintain Forum Content Quality
On the brand’s digital platforms, users generate a huge amount of data on a daily basis. It gets really hard for the brands to keep track of the content generated on these platforms and give quick responses. Natural language processing technology has proved to be an effective tool for businesses that have to deal with large volumes of user-generated content. This tool allows companies to connect and engage with their customers more effectively. Using this tool, businesses can respond to the queries and questions of customers on time which helps them develop better customer relationships.
NLP is also good at detecting malicious and spam content. It automatically filters and blocks unsolicited content from the brand’s social media pages and website. Businesses can use NLP technology to maintain the quality of their user-generated content. It ensures that there are no unwanted ads or spiteful backlinks.
6. Higher Search Engine Ranking
You might be thinking about how a Natural language processing model can help your website rank high on search engine results. For any business, search engine ranking is a critical factor in determining its success in the market. To enhance their online visibility, companies hire SEO experts. NLP models can detect the search queries and suggest the relevant keywords that make the research convenient and hassle-free. It not only saves a lot of time but also optimizes your content and improves the SEO of your website. NLP technology allows you to better target the keywords that also support you in creating focused marketing campaigns that would capture the attention of maximum customers on search engine pages.
7. Predictive Text
NLP technology does not just deal with speech recognition, but mobile companies also use it as text predictive in autocorrects and autocomplete. We have been using these features for a while now texting on smartphones. Autocorrect makes your SMS more sensible and removes errors. The search engine also uses these features to make online searches easier and more convenient. For instance, on Google when you type a keyword, it autocompletes the word in the search bar and also gives you a different suggestion list related to that keyword. The best thing about these autocorrect and autosuggestion features is that they learn from you. Over time, as you keep using these features, they automatically customize themselves to the preferences and style of every individual.
Significance of NLP in Global Communication
Considering the benefits of NLP for businesses, we can say that it has revolutionized global business communication. There is a major shift in the way businesses interact with their customers and vice versa. Whether it is customer support or moderate user-generated content, NLP has the capacity to manage everything quite effectively. Chatbots are the major example in this case. The way NLP chatbots have revolutionized the customer support sector is commendable.
It has made it easier and more convenient for businesses to communicate with their customers in real time. The online customer experience has also significantly increased after employing NLP in the business sector. Customers can now better interact with online applications and websites, and they also get quick and relevant responses.
Following are some powerful techniques Natural language processing uses to give a boost to global business communication.
1. Name Entity Recognition
In this NLP technique, the main entities presented in the text are extracted. These entities can be the names of persons, names of the country, names of brands, etc. Once all entities are identified, the NLP algorithm can make better sense of the sentences.
2. Stemming and Lemmatization
In the stemming technique, inflected words are reduced to their root form, cutting down all the suffixes and prefixes. The purpose of lemmatization is to keep the context intact. In this process, all inflectional endings are eliminated and returned to the dictionary word that is closer to the context.
3. Natural Language Generation
In this process, NLP converts the structured data into natural languages; it can be English or any other language. It helps the algorithm recognize the patterns and gain a better understanding of the data.
4. Sentimental Analysis
As the name suggests, this technique detects the emotions and sentiments behind the speech or text by using emotion AI. Companies use this technique to improve customer service efforts.
5. Sentence Segmentation
In the end, all the text, derived from the avid processes, is segmented into meaningful sentences and phrases. At this stage, the NLP algorithm adds punctuation marks to make it readable for humans.
Final Words!
NLP technology is becoming a significant part of many companies around the world because of its significance. This technology has literally transformed global communication, customer service, customer experience, and business conversion rates. Companies are adopting this advanced technology to save up their time, cut down costs, and generate more revenue. Businesses leverage NLP technology to detect the sentiments and pain points of their customers and improve their services accordingly. Natural language processing with AI is taking over the business world, making it more convenient for companies to manage their customers and enhance their overall online experience. It is also shaping the future of multilingual communication worldwide because of its data intelligence and powerful algorithms.
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