revise my essay

Abstract

I chose it because I believe that in the 21st century, artificial intelligence has gradually entered our lives and is closely connected. Language-communication is a behavior that people need every day, but it is very difficult for machines to communicate with us by writing programs, and the diversity of language environments around the world makes this idea even more difficult. I will focus on the research of artificial intelligence on Chinese language. As far as I know, the language environment in China is quite rich, even though the common language is Mandarin. However, due to different regions, China has produced ten different dialects. Because of the different pronunciations, artificial intelligence has also encountered difficulties in mastering these dialects. Because the goal of our team is how artificial intelligence accepts and masters our language, the current understanding and use of different languages by robots has indeed become a problem. (For example, each country has different rhetoric techniques, for example, the same word in China has different meanings due to different intonations).

Keyword：Artificial Intelligence，Chinese Language.

Every country in the world has its own language, such as English, French, Russian and Chinese as we know it. English is divided into two parts, namely American pronunciation and British pronunciation. Among them, the British pronunciation is more powerful, such as "car", the British pronunciation is [ka:], and the American pronunciation is [kar]. Russian and Chinese are even more different. Russian tongue sounds are very serious, while Chinese requires continuous tongue curling to determine the pronunciation. Since the research direction of this article is Chinese, I will focus on the usage of Chinese vocabulary.

Regarding Chinese, I think everyone will know something about it. Many Americans have one or two Chinese words, such as "nihao", which means hello. This is not a difficult vocabulary, and you can learn it without excessively rolling your tongue. But "erduo" or "ear" is a typical tongue-rolling pronunciation. But the difficulty of learning Chinese does not stop at this point. In the book "Chinese Lexical Semantics", it is written that the word "zenme" is a common word in Chinese sentences. It has many meanings, such as "how", " why". Next I will explain their usage. From Ben Liu (Department of Chinese Language & Literature, Peking University, 2015，p74).

“1. 他 怎么 学会 广州话 的？

he how master Cantonese DE?

How did he master Cantonese?

2. 这 事 我 该 怎么 跟 他 说？

this I should how to he say?

How should I tell him about this?”

As you can see, the above sentence indicates that "zenme" cannot be used before the verb. It is relatively rigid, but the following ions will be used in another way. From Ben Liu (Department of Chinese Language & Literature, Peking University, 2015，p75).

"1. 他 怎么 这么 高兴？

he why so happy?

Why was he so happy?’

2. 小李 怎么 没 报名？

XiaoLi why NEG sign up?

Why didn’t XiaoLi sign up?’

3. 怎么 他 还 不 出来？

why he yet NEG come out?

Why hasn’t he come out yet?"

From these sentences, you can see that "zenme" can be used in front of verbs or adjectives. You should already know that "zenme" in the second sentence is more semantically flexible than the first example. The first example can be used In the future tense and the past tense, but in the second example "zenme" is usually only used in the past tense.

·In the 21st century, artificial intelligence has been widely used in various fields. Google translation, which is often used around us, is a good example. It can use the database created by programmers to match multiple languages to achieve different languages. The targeted translation of "AI still doesn't have the common sense to understand human language" written by Karen Hao (2020) mentioned that effective progress has been made in the field of natural-language processing (NLP), but only through the database The update to match the language, this is not a real sense of mastering a multi-language environment, it still requires human operation.

To truly master the multilingual environment, robots must be required to understand the semantic and logical relationships in different languages. Regarding the logical problems of multilingual environments, we can find clues in the article "Quantifiers in Natural Languages: Some Logical Problems, I" written by Jaakko Hibkikka. The author points out that artificial intelligence often misunderstands the correct meaning of sentences when performing semantic analysis. In these misunderstood sentences, most of the reasons come from the logic of the sentence. We can understand it in this way, comparing language to symbols. When the robot masters the symbols, they also know what the symbols express. The most important feature of symbols is subjectivity or arbitrariness. For example, we often say that roses represent love. In fact, there is no inevitable connection between roses and love (the natural attributes of roses do not include representing love). Subjective logic gives this connection and makes it a logical idea for the entire society.

An important branch in the field of artificial intelligence, Natural Language Processing (NLP). NLP starts from the perspective of computer science and is considered a sub-discipline of computers. The purpose of NLP is to efficiently process natural language algorithms. For example, Chinese word segmentation based on character sequence annotation, Among them, Multi-task learning (MTL) is the mainstream force in the NLP language model. NLP in big data computing has achieved great results, but it relies heavily on artificial means, and in contrast, there is much less in-depth linguistic thinking.

Or it has warned the world that the rapid development of artificial intelligence will affect the world. In 2020, we will become accustomed to artificial intelligence around us, siri, smart homes, and smart replies on web pages. Although the artificial intelligence in science fiction movies is out of control and super high IQ is still a long way away, with the development of technology, this is not impossible. A very simple example, you ask Siri if you can bbox, siri will perform a singing session, some netizens found that this phenomenon did not start with a system update, or that the robot has been completed by the self-upgrading code written for them by the researcher Self-upgrading? The most famous example is that machine learning experts from the British company Swiftkey created a learning program. This technology has been used as a smart phone keyboard application, which can learn the user's ideas and suggest the next word.

Work Sited