This paper presents an in-depth study and analysis of the model of English writing using artificial intelligence algorithms of neural networks. Based on word vectors, the unsupervised disambiguation, and clustering of multimedia contexts extracted from massive online videos, the disambiguation accuracy reaches over 0.7, and the resulting small-scale multimedia context set can cover up to 90% of vocabulary learning tasks; user experiments show that the multimedia context learning system based on this method can improve the effectiveness and experience of ESL vocabulary learning, as well as the long-term word sense memory of learners. The results are 30% better. Based on the dependency grammatical relations and semantic metrics of collocations on a large-scale professional corpus, we established a collocation intention description and retrieval method in line with users’ linguistic cognition and doubled the usage rate of collocation retrieval on the actual deployment system after half a year, becoming a user “sticky” ESL writing aid, and further defined style. Dictionaries only provide basic lexical definitions, and, even if supported by example sentences, they still cannot meet the needs of ESL authors in terms of expressive accuracy and richness. However, the current machine translation is based on the black box deep neural network construction, and its translation process is not understandable and interactive. Among the three algorithmic models constructed in this paper, the multitask learning model outperforms the conditional random field model and the LSTM-CRF model because the multitask learning model with auxiliary tasks solves the problem of sparse data to a certain extent, allowing the model to be trained more adequately in the case of uneven label distribution, and thus performs better than other models in the task of grammatical error detection.
Based on the existing optimization neural network algorithm, this paper introduces a simple and computationally efficient adaptive mechanism (adaptive exponential decay rate). By applying the adaptive mechanism to the Adadelta algorithm, it can be seen that AEDR-Adadelta acquires the learning rate dynamically and adaptively. At the same time, by proposing an adaptive exponential decay rate, the number and method of configuring hyperparameters can be reduced, and different learning rates can be effectively obtained for different parameters. The model is based on the encoder-decoder structure and adopts a dual-encoder structure. The transformer encoder is used to extract the context information of the sentence; the Bi-GRU encoder is used to extract the information of the source sentence; and the gated structure is used at the decoder side. The input information is integrated, and each part is matched with different attention mechanisms, which improves the model’s ability to extract and analyze relevant features in sentences. In order to accurately capture the coherence features in English texts, an improved subgraph matching algorithm is used to mine frequently occurring subgraph patterns in sentence semantic graphs, which are used to simulate the unique coherence patterns in English texts, and then analyze the overall coherence of English texts. According to the frequency of occurrence of different subgraph patterns in the sentence semantic graph, the subgraphs are filtered to generate frequent subgraph sets, and the subgraph frequency of each frequent subgraph is calculated separately. The overall coherence quality of English text is quantitatively analyzed by extracting the distribution characteristics of frequent subgraphs and the semantic values of subgraphs in the sentence semantic graph. According to the experimental results, the algorithm using the adaptive mechanism can reduce the error of the training set and the test set, improve the classification accuracy to a certain extent, and has a faster convergence speed and better text generalization ability. The semantic coherence diagnosis model of English text in this paper performs well in various tasks and has a good effect on improving the automatic correction system of English composition and providing reference for English teachers’ composition correction.
Under the pressure of global industrial competition in the 21st century, perceptual design has become a prominent subject in the field of design. With the progress of science and technology and the improvement of people's life quality, modern consumers have gradually become more and more sensitive to the demands of products. It is an important subject for modern designers to design products more in line with consumers' demands through Kansei Engineering. Through the discussion of relevant literature data, this paper sorts out the theories and methods of Kansei Engineering and the practice and application of perceptual design. Firstly, this paper discusses the fashion significance of the Age of Sensibility, describes the theories, types and methods of Kansei Engineering, and the relationship between Kansei Engineering and fashion. Secondly, it explores the perceptual aesthetic style, describing that style is composed of aesthetic elements such as shape, color and texture. Third, the paper focuses on the marketing and strategy in the Age of Sensibility, aiming to point out that consumers' motivation to buy goods is not just the use function of goods. Aesthetic marketing strategy is to establish a series of aesthetic marketing strategies based on the five senses (vision, hearing, smell, taste and touch) of the perceptual experience generated in the enterprise brand. Fourth, the paper expounds that designers should grasp the sense perception and psychological needs of customers, systematically implant the user's needs into the prototype design, and make the perceptual design the key to adding value of creative economy, aesthetic economy and knowledge economy.
The human world is a world of symbols, which originates from the natural physiological response of human body and forms the public behavior through common cognition. The use of symbols contributes to the communication mode of consciousness information expression. Decoration is a symbol in the world of colorful symbols, an indispensable and necessary part of life. In addition to keeping warm, protecting the body and beauty, it is also a form of human expression of emotion and self-expression, and also shows the features of all social classes. The Rukai nationality in Taiwan is an ethnic group without written language. The application of pattern implies the social class, customs and cultural context of the ethnic group. Based on the relevant literature records, field records, field interviews and comprehensive analysis, this paper discusses the pattern decoration of Rukai nationality from the perspective of semiotics: the nature, origin and significance of behavior of marks. It is hoped to arouse people's understanding of the traditional pattern decoration of the Rukai people in Taiwan, and to care about their traditional culture and inheritance.
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