歌词——情感的点与面

歌词是一种重要的音乐文学形式,在创作中其对感情的表现不同于单纯的文学创作,有自己的艺术特点、艺术规律。那么,如何才能创作出有利于配乐的歌词？本文从为音乐创作提供感情脉络、感情线索的角度,提出了要捕捉好情感生发变化的点、描绘好情感的多个侧面及多重色彩、揭示好情感矛盾的相互关系的观点,并结合古今优秀歌词进行了分析论证。

自能语文：以点线面的方法引导理科生鉴赏诗歌

在选课走班模式下的语文学习更关注学生的个体差异。理科学生大多存在读不懂诗歌,或不会鉴赏诗歌的问题。在诗歌教学过程中尝试用"意象点--脉络线--情感面"的方法引领理科生鉴赏诗歌。用相对明快的步骤、简洁的分析、干练的术语引领理科生读懂诗歌。

情感类课文教学策略研究

语文教材是充满情感的，语文教学要利用教材对学生进行情感的熏陶。教师在教学中，要充分利用教材，从把握情感脉络入手，分清人物的情感块面，在品味情感亮点中，获得文本情感的滋养。

The Emotional Approach of Foreign Vowel Acquisition Within the Example of British English Vowels

The aim of the article is to present results of research that was performed with 97 Polish students of the second and third year of English Philology. The purpose of the research is to examine how conscious manipulation of facial expressions aids acquisition of foreign vowels by learners, regardless of their native language and the culture they have been brought up in. Taking advantage of achievements derived from such disciplines as psychology of emotions and phonetics depicted as a physical process, an attempt is made to find a tool that improves teaching/learning of foreign vowels, that is to say, an effort is put in search of a useful method to make the phonetic process faster and more accurate. Teachers of English are encouraged to put the method, which is described in detail in the paper, into practice with their own mother languages and to share opinions about the method with colleagues. Similarly, it is believed that it can be applied to courses of other languages than just English. Teachers of those languages are encouraged to try to use it, too.

Cognitive Emotion Model for Eldercare Robot in Smart Home

Based on the smart home and facial expression recognition, this paper presents a cognitive emotional model for eldercare robot. By combining with Gabor filter, Local Binary Pattern algorithm(LBP) and k-Nearest Neighbor algorithm(KNN) are facial emotional features extracted and recognized. Meanwhile, facial emotional features put influence on robot's emotion state, which is described in AVS emotion space. Then the optimization of smart home environment on the cognitive emotional model is specially analyzed using simulated annealing algorithm(SA). Finally, transition probability from any emotional state to a state of basic emotions is obtained based on the cognitive reappraisal strategy and Euclidean distance. The simulation and experiment have tested and verified the effective in reducing negative emotional state.

Study of the affective interaction in college English teaching

Affect plays a significant role in college English teaching and learning, in which teachers, learners, tasks and contexts or environments interact with each other, developing a system of affective interaction. In the system, the teacher is a facilitator and mediator and the learner is the subject of English learning. In a harmonious and friendly classroom environment, with the knowledge transmission blending in well with the cultivation of affect, attitudes and values, students＇ cognitive and emotional development can be promoted. The experimental results of the present study indicated that students in the affective college English classroom did significantly better （p〈 .05） in cognition than before. Furthermore, the analyses of the two surveys showed that attention to affective interaction in college English teaching helped students enhance their interest in college English learning, cross-cultural awareness, self-confidence, interpersonal intelligence, and so forth. Therefore, our conclusion is that attention to affective interaction in college English classroom teaching is conducive to students＇ personal growth and a more holistic development.

Analyzing Kansei from Facial Expressions by CSRBF Mapping

This paper describes an application where a new KAE （Kansei/Affective Engineering） system was applied to define the properties of the facial images perceived as Iyashi. Iyashi is a Japanese word used to describe a peculiar phenomenon that is mentally soothing, but is yet to be clearly defined. Instead of analyzing facial expressions of an individual to determine his emotional state, the proposed system introduces a FQHNN （fuzzy-quantized holographic neural network） to find the rules involved in the Kansei evaluation provided by the subjects about the limited dataset of 20 facial images. In order to validate and gain a clear insight into the rules involved in the Kansei evaluation process, Procrustes analysis and CSRBFs （compactly-supported radial basis functions） are combined to generate new facial images. Procrustes analysis is used to find the minimal dissimilarity measure between two facial images with opposite classification （i.e., Iyashi and Non-lyashi）. CSRBFs are proposed for tuning of 17 facial parameters and mapping between facial images within opposite classes. The experiments with two subjects demonstrate that if only two from the five most important parameters of the face are changed, then the Kansei evaluation can change to the opposite class. This paper shows that a continuous and efficient tuning of the design space can be achieved by introducing CSRBF mapping into the new KAE system.

Using Kinect for real-time emotion recognition via facial expressions

Emotion recognition via facial expressions （ERFE） has attracted a great deal of interest with recent advances in artificial intelligence and pattern recognition. Most studies are based on 2D images, and their performance is usually computationally expensive. In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression features captured by Kinect sensors. To capture the deformation of the 3D mesh during facial expression, we combine the features of animation units （AUs） and feature point positions （FPPs） tracked by Kinect. A fusion algorithm based on improved emotional profiles （IEPs） arid maximum confidence is proposed to recognize emotions with these real-time facial expression features. Experiments on both an emotion dataset and a real-time video show the superior performance of our method.