Ecologically sustainable development is the environmental basis of sustainable development. In order to realize ecological sustainable development, we need to study the mental health status of college Chinese learners under the principle of prevention. This study analyzes the correlation and cognition between college Chinese learners’ mental health and their mental health status during the learning time through statistical methods and different personalities under various factors. The results show that the learners’ mental health state in learning college Chinese is different, the percentage of different personalities under certain factors is different, the relevance and recognition in the learning process are indispensable, and the effect is often different in the length of the learning time, so it is of great significance to the learners’ mental health state.

With the advancement of globalization, an increasing number of people are learning and using a common language as a tool for international communication. However, there are clear distinctions between the native language and target language, especially in pronunciation, and the domestic target language, the learning environment is far from ideal, with few competent teachers. In addition, such learning cannot achieve computer-assisted language learning (CALL) technology. The efficient combination of computer technology and language teaching and learning methods provides a new solution to this problem. The core of CALL is speech recognition (SR) technology and speech evaluation technology. The development of deep learning (DL) has greatly promoted the development of speech recognition. The pronunciation resource collected from the Chinese college students, whose majors are language education or who are planning to obtain better pronunciation, shall be the research object of this paper. The study applies deep learning to the standard but of target language pronunciation and builds a standard evaluation model of pronunciation teaching based on the deep belief network (DBN). On this basis, this work improves the traditional pronunciation quality evaluation method, comprehensively considers intonation, speaking speed, rhythm, intonation, and other multi-parameter indicators and their weights, and establishes a reasonable and efficient pronunciation model. The systematic research results show that this article has theoretical and practical value in the field of phonetics education.

In recent years, neural network-based English-Chinese translation models have gradually supplanted traditional translation methods. The neural translation model primarily models the entire translation process using the “encoder-attention-decoder” structure. Simultaneously, grammar knowledge is essential for translation, as it aids in the grammatical representation of word sequences and reduces grammatical errors. The focus of this article is on two major studies on attention mechanisms and grammatical knowledge, which will be used to carry out the following two studies. Firstly, in view of the existing neural network structure to build translation model caused by long distance dependent on long-distance information lost in the delivery, leading to problems in terms of the translation effect which is not ideal, put forward a kind of embedded attention long short-term memory (LSTM) network translation model. Secondly, in view of the lack of grammatical prior knowledge in translation models, a method is proposed to integrate grammatical information into translation models as prior knowledge. Finally, the proposed model is simulated on the IWSLT2019 dataset. The results show that the proposed model has a better representation of source language context information than the existing translation model based on the standard LSTM model.

Peribahasa berkaitan dengan budaya dan bahasa suatu bangsa. Peribahasa Indonesia berjumlah banyak, di antaranya yang mengandung unsur makanan dan cita rasanya. Makanan merupakan kebutuhan pokok, cermin budaya, dan tradisi bangsa. Peribahasa Indonesia mengandung nilai karakter yang sesuai dengan profil pelajar Pancasila, yaitu beriman, bertakwa kepada Tuhan YME, berakhlak mulia, berkebinekaan global, bergotong royong, mandiri, bernalar kritis, dan kreatif. Artikel ini difokuskan pada (1) analisis jumlah peribahasa Indonesia yang mengandung unsur makanan, jenis makanan, dan cita rasanya; (2) analisis nilai karakter dalam peribahasa Indonesia yang berunsur makanan dan cita rasanya yang sesuai dengan profil pelajar Pancasila. Penelitian ini mengombinasikan metode kualitatif dan kuantitatif. Hasil penelitian menunjukkan bahwa (1) terdapat 388 peribahasa yang mengandung unsur makanan dan cita rasanya; (2) diketemukan peribahasa yang sesuai dengan nilai karakter dalam profil pelajar Pancasila, kecuali nilai karakter berakhlak mulia terhadap alam.

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