Natural language processing, the core technology of conversational artificial intelligence, is a technology that enables computers to understand and communicate with human language, recognizing speech and understanding meaning to give accurate answers and perform tasks. This technology is used in various fields such as searching, analyzing information, and providing customized services, and is being developed with the goal of enabling free communication between AI and humans and improving the quality of life.
Conversational A.I., which not only searches and answers questions but also performs various tasks according to the intent of the user’s words, has taken the world by surprise. Apple’s Siri, Samsung’s S Voice, LG’s Q Voice, and many other companies have introduced AI-based interactive applications, and recently, Naver unveiled Naver i, which surpasses Google’s voice recognition technology, and many IT companies are developing conversational AI. Natural language processing (NLP) is the key to this technology. In order to further improve the functions of conversational AI, advanced natural language processing technology is required, so global companies are researching this field. How does natural language processing allow computers to understand human speech, and why is it such an important technology that companies are rushing to develop it?
Natural language processing is the technology that enables computers to understand natural language, or human speech. Whereas speech recognition technology simply translates human speech into text, natural language processing involves determining the meaning or intent of the speech. For a computer to understand natural language, it’s a bit like putting together a puzzle. First, the computer recognizes human speech in syllables and combines them to form morphemes. For example, if you say, “I want an apple,” it will recognize “apple+” as the most appropriate morpheme combination of “apple” and “apple+” or “apple+” and “apple+”. The morphemes are analyzed to determine their respective parts of speech, i.e., ‘apple’ is a noun, and ‘on’ is an article. Then, the morphemes are combined according to their parts of speech, and the role of the combined phrase in the sentence is determined, i.e., whether ‘apple’ is the subject or the object. Finally, it understands the meaning and intent of the sentence by identifying the semantic relationship of the phrases and responds or performs an action accordingly.
This process of natural language processing plays an important role in helping machines understand and utilize human language. This is because language is not just a combination of symbols, but requires an understanding of the culture and context in order to be interpreted correctly. For example, the sentence “It’s windy” may simply describe the weather, but it can also have a poetic or metaphorical meaning. For a computer to understand this contextual meaning, it requires a huge amount of data and complex algorithms. This is where deep learning technology comes in, and systems are being built that allow computers to learn and evolve on their own.
While it may seem simple at first glance, it’s not easy to translate ambiguous and ambiguous natural language into machine language that is disambiguated by context. Even a simple sentence like ‘I like delicious pears’ poses a problem for natural language processing. We immediately understand that a pear is a fruit, but in reality, it can be a mode of transportation or a body part. In order for a computer to naturally understand the sentence above, it would need to infer that pears are a fruit from the semantic relationship with the preceding phrase, “delicious,” based on the knowledge that pears are eaten and that many people find them delicious. Natural language processing of ambiguous sentences such as the above is still lacking, and natural language processing technology needs to be further developed to solve this problem.
Natural language processing technology plays an important role in the development of A.I. to the point where it can communicate with humans. However, natural language processing is not just for AI to communicate with humans. Natural language processing is used across all areas of AI, most notably in search and information analytics. In search, natural language processing can help users find the information they’re looking for efficiently. Natural language processing accurately identifies the intent of the user’s search and analyzes a large number of natural language materials in the database to output the most appropriate results. For example, if you search for ‘restaurants in Seoul National University,’ A.I. doesn’t just look for those words in the database, but also understands the intention of what you want to get from the search and provides information such as location, price range, and atmosphere.
As in the example above, it is important for A.I. to understand the characteristics of the user in order to provide optimized information. To do this, AI analyzes user information such as search history, and natural language processing plays a big role in this area. Data analysis is not only used to help users search smoothly, but also to analyze reviews and opinions of users and help A.I. improve itself. These data analytics techniques can be used in a variety of fields, including healthcare, finance, and education. For example, in the medical field, it can be used to analyze patient records to provide customized treatment, or in the financial field, it can be used to analyze market trends to help develop investment strategies. As such, natural language processing is an important technology that can maximize the effectiveness of AI in various fields.
Until now, AI and humans have lived separately, like foreigners, because they speak different languages. Only a few people with specialized skills could handle AI, and most of the rest of us could only communicate with it through them. Now, however, natural language processing is building a bridge between the two. AI and humans can communicate through human language without having to rely on any other medium. Natural language processing has made it possible to bring AI from the realm of distant science fiction movies to the realm of interactive applications like the ones mentioned above. Of course, the conversational AI developed to date has not yet reached the stage where it can communicate with humans seamlessly. However, as the world recognizes the importance of natural language processing technology and invests heavily in it, it is expected that the day will come when A.I. will be able to have natural conversations with humans. In such a future, AI and humans will be able to communicate freely and develop together. Furthermore, these technologies will play a major role in improving the quality of human life and solving complex problems. For example, AI can analyze and understand complex legal documents through advanced natural language processing, making legal services more accessible to the general public. In the education sector, natural language processing has the potential to revolutionize many fields, such as analyzing students’ learning styles to provide customized educational programs.
