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AI-based systems make our lives more convenient every day. One of the technologies that is drawing attention in the fields related to AI is natural language processing (NLP). It is applied to AI assistants such as Siri and Alexa and real-time translation functions and is expected to be used in the business field. This time, we will introduce basic knowledge and application examples of AI and natural language processing.
Basic knowledge of natural language processing
Here, I will explain the basic knowledge of natural language processing.
What is natural language processing?
According to “Introduction to Natural Language Processing: 1. An Overview of the Current Situation and History” (Okada and Nakamura. Journal “Information Processing”. Introduction to Natural Language Processing: 1. An Overview of the Current Situation and History. 1993,11, p1385-1386) “Natural Language Processing is the processing of artificial languages such as programming languages by computer, such as Japanese, English, and Russian, which people speak and write on a daily basis.” There is.
Relationship between natural language processing and AI / machine learning
The data obtained in the process of natural language processing can be applied to AI assistants and machine translation by utilizing machine learning, which is an elemental technology of AI.
Background of attention to natural language processing
There are three main reasons why natural language processing is attracting attention.
- Increase in text data
- Declining working population
- Promotion of technological innovation
Increase in text data
The first is the increase in text data around us. Recently, various communication tools have appeared, and text-based communication has increased. For example, enterprises have introduced communication tools such as “Chatwork” and “Teams” to facilitate web meetings and chat interactions. Furthermore, the digitization of conference data is progressing, such as recording and transcribing web conferences. It is necessary to utilize such text data not only in business but also in daily life.
Declining working population
Second, the working population is declining. AI assistants and machine translations that apply data obtained from natural language processing are attracting attention because they replace human work.
Promotion of technological innovation
The third reason is that technological innovations in natural language processing are being promoted worldwide. For example, in 2018, Google announced a natural language processing model called “BERT (Bidirectional Encoder Representations from Transformers)”. Google has announced that BERT can enable “reading context” that was difficult with traditional natural language processing models.
Examples of using natural language processing
There are six main use cases for natural language processing.
- Chatbot
- Text mining
- Email filter
- Character conversion prediction
- Smart assistant
- Machine translation
Chatbot
Chatbots are systems that return answers to the information you enter. Mainly, voice data such as Siri and Alexa are analyzed by natural language processing, and AI responds appropriately. “Smart Robot” is one of the services that utilize chatbots. SmartRobot is an interactive AI chatbot service from Taiwan. It is known as a service that can automate customer service and improve the efficiency of internal operations. In addition, machine learning improves the accuracy of conversations, and by promoting natural communication, it is possible to efficiently respond to customers.
Text mining
Text mining is the extraction of important information from a large amount of text data. In natural language processing, documents are divided according to the steps of “morphological analysis, parsing, semantic analysis, and context analysis”, and information judged to be important is extracted from them. Text mining is a technology that is also used in big data, and it is also applied to marketing because it can analyze text data for customer interactions and inquiries.
Email filter
The mail filter is a system that analyzes the text of the sent mail and automatically sorts it when it recognizes spam mail or unsolicited mail. Email filters are one of the basic examples of online natural language processing applied online from the early days. One of the services that utilize the mail filter is “Gmail” provided by Google. Gmail categorizes email into one of the “Main Social Promotions” categories. When classifying, the body of the email is analyzed and received in the appropriate category.
Character conversion prediction
Natural language processing is also used to predict character conversion on personal computers and smartphones. When you enter Hiragana characters, the natural language processing function is used as a function to convert them into Chinese characters, emoticons, or pictograms. “ATOK Lab” is also a service that utilizes character conversion prediction. ATOK Lab is a mechanism that recognizes the language itself, not just character conversion. For example, the proofreading support function for sentences. As a result, not only the mistakes in the characters but also the accuracy of the sentences are improved.
Smart assistant
Smart assistant is a service that utilizes voice recognition such as “Siri” implemented on iPhone and “Alexa” provided by Amazon. The smart assistant analyzes human words by natural language processing and returns the answer with the closest meaning. For example, if you are an iPhone user, you can call “Hey Siri” and ask “What is the weather tomorrow?” And it will answer the weather tomorrow.
Machine translation
Natural language processing is also used for machine translation such as Google Translate. With the evolution of natural language processing, translations that are close to general expressions have become possible. Before the introduction of natural language processing, when translating from Japanese to English, it was translated without being conscious of grammar. Recently, a high-precision translation function called “DeepL” has appeared. Since DeepL can translate document files as they are, there is no need to recreate them for translation, and the translation function can be used efficiently.
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summary
The process of natural language processing by AI has become an important technology that supports AI assistants and machine translation. The use of AI, including natural language processing, requires the cost of hiring and developing specialized human resources. UMWELT allows anyone to easily analyze data using AI with no code. If you are thinking of introducing an AI system, please consider UMWELT.
