Application of artificial intelligence technology in the field of linguistics

In the early 1990s, Mr. Zhou Haizhong, a famous Chinese scholar, once predicted that artificial intelligence technology will be widely used in various disciplines and will produce unexpected effects. Today, more and more facts prove his prediction. Relevant experts pointed out that artificial intelligence technology has unlimited potential and has broad application prospects in the field of linguistics. It will become an important driving force for a new round of scientific and technological revolution and industrial transformation.

Artificial intelligence technology is an important branch of computer science and belongs to the three-way interdisciplinary discipline of natural science, social science, and technical science; it started in the last century It has shown strong vitality since its birth in the 1950s, and developed rapidly in the late 1980s thanks to the rapid development of computer software and hardware. As the hottest technology in the current scientific and technological field, artificial intelligence technology has attracted the attention of many people inside and outside the industry; it has also penetrated into the academic field and is playing a role in the academic field in various ways. At present, artificial intelligence technology includes five major parts: big data, speech recognition, machine learning, computer vision, and natural language processing. Artificial intelligence technology is mainly built on the basis of machine learning, and machine learning not only requires reasonable, applicable and advanced algorithms and computing power, but also relies on good enough and sufficient data.

Artificial intelligence technology is a simulation of human intelligence phenomena, including the simulation of human thinking processes; it involves computer science, psychology, linguistics and other disciplines. The development of artificial intelligence technology does not seem to follow an evolutionary process from low-level to high-level, but will suddenly become much "smarter" than humans at some "points", that is, in a single dimension. Human intelligence is comprehensive and multi-dimensional. Perhaps our learning, memory, information search, decision-making, judgment or processing abilities are not the most remarkable. AlphaGo has proven that we humans may not be as good as the artificial intelligence technology produced by deep learning in these aspects.

Linguistics, as the name suggests, is the subject of studying natural language (that is, the language that people use daily); however, linguistics does not refer to the process of learning one or more specific languages. The task of linguistics is to study and describe the structure, function and historical development of language, reveal the essence of language, and explore the common laws of language. Because only human beings have language and use sound language to communicate, through the study of language, we can understand more clearly the position of human beings in the world or universe, and thus understand the nature of human beings more thoroughly. Language is an important criterion for distinguishing human beings from all things. Machine understanding of human language is the last challenge of artificial intelligence technology, and it is also the most difficult challenge. It can be said that natural language is the highest level abstract expression of human intelligence.

Linguistics, as the science of studying natural language, has a very ancient history; the earliest human language research began with the interpretation of ancient documents, and was studied for the purpose of studying philosophy, history and literature. linguistic. Various human intelligences are closely related to language; language is a unique communication method for human beings. It reflects the highly evolved mental abilities of human beings at the biological or psychological level, and reflects the progress of human civilization at the social and cultural level. Linguistics is the study of the core instinctive language ability of human beings. Through the analysis and research of spoken language, written language and even sign language, we can understand the nature of human beings. In addition to understanding the nature of human beings, linguistic research also has many application values.

Human thinking process can be understood as a computational process of symbol processing; human language understanding process can also be understood as a computational process in knowledge representation, which enables computers to understand natural Language is technically possible. Therefore, the cognitive study of language naturally extends to the computational analysis of language. It can be said that the ability to process language is an advanced form of artificial intelligence technology. Although there are important differences between linguistics and artificial intelligence technology, their research is closely related; they promote each other and develop together. From a theoretical and applied perspective, there are currently at least the following branches of linguistics related to artificial intelligence technology.

Computational Linguistics

Computational linguistics is an emerging discipline rooted in the fertile soil of computer science, linguistics, mathematics and other disciplines. It analyzes and processes natural language by establishing formal mathematical models, and uses programs on computers to realize the analysis and processing process, thereby achieving the purpose of using machines to simulate part or even all of human language abilities. Its projects include statistical data, retrieval of information, research on lexicon and syntax, recognition of text, synthesis of speech, preparation of machine-assisted teaching programs, machine-assisted translation, etc. Having the perception and understanding of language is the basis of language computing. The close connection between language and thinking, the variability, variability and introspection of language are not grasped and known by people. The main purpose of computational linguistics is to solve problems in linguistics with the help of models and algorithms in the fields of computer science and statistics. It can be seen that artificial intelligence technology plays a decisive role in computational linguistics research.

Natural language processing (NLP) is an important research topic in computational linguistics. It mainly studies how to use computers to understand and generate natural language. Achieving natural language communication between humans and computers means enabling computers to both understand the meaning of natural language texts and to express given intentions, thoughts, etc. in natural language texts. The former is called natural language understanding, and the latter is called natural language generation. The purpose of natural language processing is to use efficient algorithms to process natural language. However, it is very difficult to achieve natural language understanding and natural language generation. The root cause of the difficulty is the widespread existence of various problems at all levels of natural language text and dialogue. Various ambiguities or ambiguities.

Cognitive Linguistics

Cognitive linguistics is mainly established under the theoretical background of cognitive science. At the same time, there are also simultaneous developments between the two. A mutually reinforcing relationship. Cognitive science not only promotes the development of cognitive linguistics and becomes the main theoretical basis of the latter, but also draws on the research results of cognitive linguistics. Cognitive linguistics has become one of the main components of cognitive science. Therefore, many scholars regard cognitive linguistics as a branch of cognitive science and as a borderline discipline between cognitive research and linguistics. The characteristic of cognitive linguistics is that it regards people's daily experience as the basis of language use, and focuses on elucidating the inseparable connection between language and general cognitive abilities. Artificial intelligence simulates human cognitive and communication processes, which can help us better reveal the essential laws of language and thus better understand human intelligence. It can be said that artificial intelligence technology plays a very important role in cognitive linguistics research.

Cognitive linguistics involves artificial intelligence, linguistics, psychology, systems theory and other disciplines. It focuses on generative linguistics and proposes the creation, learning and application of language from the basics. Everything must be explained through human cognition, because cognitive ability is the foundation of human knowledge. Cognitive linguistics is a guiding ideology for building operating systems for artificial intelligence technology. It is conceivable that in the future, our interaction with artificial intelligence technology will no longer be a line of commands, but more like communication between people; this requires that the technology must have language capabilities. In addition, language also plays a role in guiding cognition and thinking. This shows the importance of cognitive linguistics to artificial intelligence technology.

Geriatric Linguistics

Geriatric linguistics, as the name suggests, is the subject that studies the language problems of the elderly. It mainly studies the nature, structure and changing rules of the language system used by the elderly and speech communication issues. The basic contents of the research include the phonetics, phonemes, vocabulary, grammar, rhetoric, writing, etc. of the elderly, as well as the flexibility of the language style of the elderly, reading skill impairment, and the loss of the second language of the bilingual elderly. In terms of application, geriatric linguistics also includes foreign language learning and successful aging, elderly care communication, hospice care and bereavement comfort, etc. As age increases, the elderly population will experience language decline and even language impairment. The research and application of geriatric linguistics are attracting increasing attention. Intelligent detection and intervention of diseases in the elderly is one of the core contents of smart medical care, and artificial intelligence technology can provide assistance in this regard.

The research on geriatric linguistics has an interdisciplinary nature, involving multiple fields such as linguistics, cognitive science and brain science, and is also closely related to artificial intelligence technology. Issues such as the neural mechanisms, disease pathology, treatment and rehabilitation of language ability decline in normal elderly people and elderly people suffering from neurodegenerative diseases belong to the category of brain science that studies human brain mechanisms from the molecular, cellular and behavioral levels; language and perception, memory, thinking , emotion, consciousness, etc., issues such as speech understanding and production research and speech therapy belong to the category of cognitive science; how to use modern technology to imitate the language function of the human brain and assist in the decline of language ability and its intervention, It belongs to the field of artificial intelligence research and application.

It can be seen from the above that artificial intelligence technology and linguistics are two independent but closely related research fields. The development of artificial intelligence technology needs to apply the research results of linguistic theory to the design of human-machine dialogue, so that the machine can understand verbal and rhetorical behaviors such as "greeting", "appeasement" and even "sarcasm" and "humor", and let the machine understand Really understand the complex semantics of human language, as well as the intentions and emotions behind it, and then give users anthropomorphic feedback, thereby achieving better human-machine natural language interaction effects. Similarly, artificial intelligence technology will also change the development direction of linguistic research. The traditional research method of emphasizing theoretical analysis but not examples, and sitting and thinking about sentences will gradually disappear from the stage; multi-modal research that pays equal attention to real corpus, spoken language and written language, and focuses on statistical analysis of language morphology will emerge in large numbers.

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