In English teaching and learning,listening ability is an important part of communicative competence,is a very practical integrated skill.It has been a difficult skill in second language acquisition for many students.M...In English teaching and learning,listening ability is an important part of communicative competence,is a very practical integrated skill.It has been a difficult skill in second language acquisition for many students.Many Chinese students are skilled in reading,but often they tend to neglect the listening.However,owing to the higher requirements of many English tests and the great importance in communication,students begin to pay attention to develop their English listening skills.But there are many factors affecting listening,the paper mainly focuses on linguistic factors and non-linguistic factors that affect listening,to provide a theoretical basis to help exploring ways of improving listening and comprehension skills.展开更多
In expression recognition, feature representation is critical for successful recognition since it contains distinctive information of expressions. In this paper, a new approach for representing facial expression featu...In expression recognition, feature representation is critical for successful recognition since it contains distinctive information of expressions. In this paper, a new approach for representing facial expression features is proposed with its objective to describe features in an effective and efficient way in order to improve the recognition performance. The method combines the facial action coding system(FACS) and 'uniform' local binary patterns(LBP) to represent facial expression features from coarse to fine. The facial feature regions are extracted by active shape models(ASM) based on FACS to obtain the gray-level texture. Then, LBP is used to represent expression features for enhancing the discriminant. A facial expression recognition system is developed based on this feature extraction method by using K nearest neighborhood(K-NN) classifier to recognize facial expressions. Finally, experiments are carried out to evaluate this feature extraction method. The significance of removing the unrelated facial regions and enhancing the discrimination ability of expression features in the recognition process is indicated by the results, in addition to its convenience.展开更多
文摘In English teaching and learning,listening ability is an important part of communicative competence,is a very practical integrated skill.It has been a difficult skill in second language acquisition for many students.Many Chinese students are skilled in reading,but often they tend to neglect the listening.However,owing to the higher requirements of many English tests and the great importance in communication,students begin to pay attention to develop their English listening skills.But there are many factors affecting listening,the paper mainly focuses on linguistic factors and non-linguistic factors that affect listening,to provide a theoretical basis to help exploring ways of improving listening and comprehension skills.
基金supported by National Natural Science Foundation of China(No.61273339)
文摘In expression recognition, feature representation is critical for successful recognition since it contains distinctive information of expressions. In this paper, a new approach for representing facial expression features is proposed with its objective to describe features in an effective and efficient way in order to improve the recognition performance. The method combines the facial action coding system(FACS) and 'uniform' local binary patterns(LBP) to represent facial expression features from coarse to fine. The facial feature regions are extracted by active shape models(ASM) based on FACS to obtain the gray-level texture. Then, LBP is used to represent expression features for enhancing the discriminant. A facial expression recognition system is developed based on this feature extraction method by using K nearest neighborhood(K-NN) classifier to recognize facial expressions. Finally, experiments are carried out to evaluate this feature extraction method. The significance of removing the unrelated facial regions and enhancing the discrimination ability of expression features in the recognition process is indicated by the results, in addition to its convenience.
