Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)最新文献_第7页

Recognition of abnormal vibrational responses of signposts using the Two-dimensional Geometric Distance and Wilcoxon test 利用二维几何距离和Wilcoxon检验识别路标的异常振动响应

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587837

M. Jinnai, Y. Akashi, S. Nakaya, F. Ren, M. Fukumi

引用次数: 3

Descriptive analysis of emotion and feeling in voice 声音中情绪和感觉的描述性分析

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587794

M. Shimura, Fumiaki Monma, S. Mitsuyoshi, M. Shuzo, Taishi Yamamoto, I. Yamada

{"title":"Descriptive analysis of emotion and feeling in voice","authors":"M. Shimura, Fumiaki Monma, S. Mitsuyoshi, M. Shuzo, Taishi Yamamoto, I. Yamada","doi":"10.1109/NLPKE.2010.5587794","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587794","url":null,"abstract":"Recognition of human “emotions” or “feelings” from voice is important to research on human communications. Although there has been much research on emotions or feelings in voice, definitions of these terms have been inconsistent. We reviewed previous papers in linguistics, brain science, information science, etc. and developed specific definitions for these term. In our paper, “emotion” is defined as an involuntary reaction in the human brain; it has two states: pleasure and displeasure. “Feeling” (e.g., anger, enjoyment, sadness, fear, and distress) is defined as a state voluntarily resulting from an emotion. Here, we should notice that the pleasure-displeasure direction does not always correspond to the feeling. So, our objective is to obtain sufficient amount of voice data and to analyze the relationship between emotions and feelings. In voice recording experiments, the voice database from about 100 participants with various natural feelings was constructed. A result of descriptive analysis showed that pleasure-displeasure direction did not correspond to the each feeling in 5% of voice data. This result suggested that, if an experimental situation is constructed that tends to arouse various feelings, data with less variability can be obtained. Further analysis of the characteristics of the data obtained to identify situations in which the pleasure-displeasure direction does not necessarily correspond to the basic feeling should lead to improved accuracy of voice emotion recognition.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124413153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Computerized electronic nursing staffs' daily records system in the “A” psychiatric hospital: Present situation and future prospects “A”精神病医院护理人员计算机电子日常记录系统的现状与展望

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587814

T. Tanioka, A. Kawamura, Mai Date, K. Osaka, Yuko Yasuhara, M. Kataoka, Yukie Iwasa, Toshihiro Sugiyama, Kazuyuki Matsumoto, Tomoko Kawata, Misako Satou, K. Mifune

引用次数: 4

Using cognitive model to automatically analyze Chinese predicate 基于认知模型的汉语谓词自动分析

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587843

Shiqi Li, T. Zhao, Hanjing Li, Shui Liu, Pengyuan Liu

引用次数: 0

Generating english-persian parallel corpus using an automatic anchor finding sentence aligner 使用自动锚点查找句子对齐器生成英语-波斯语平行语料库

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587769

Meisam Vosoughpour Yazdchi, Heshaam Faili

引用次数: 3

Detection of users suspected of using multiple user accounts and manipulating evaluations in a community site 检测涉嫌使用多个用户帐户和操纵社区网站评估的用户

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587765

Naoki Ishikawa, Kenji Umemoto, Yasuhiko Watanabe, Yoshihiro Okada, Ryo Nishimura, M. Murata

引用次数: 7

Extracting opinion sentence by combination of SVM and syntactic templates 基于支持向量机和句法模板的观点句提取方法

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587835

Bo Zhang, Yanquan Zhou, Yu Mao

引用次数: 5

Improving emotion recognition from text with fractionation training

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587800

Ye Wu, F. Ren

引用次数: 4

Data selection for statistical machine translation 统计机器翻译的数据选择

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587827

Peng Liu, Yu Zhou, Chengqing Zong

引用次数: 10

Research on sentiment classification of Blog based on PMI-IR 基于PMI-IR的博客情感分类研究

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587849

Xiuting Duan, Tingting He, Le Song

{"title":"Research on sentiment classification of Blog based on PMI-IR","authors":"Xiuting Duan, Tingting He, Le Song","doi":"10.1109/NLPKE.2010.5587849","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587849","url":null,"abstract":"Development of Blog texts information on the internet has brought new challenge to Chinese text classification. Aim to solving the semantics deficiency problem in traditional methods for Chinese text classification, this paper implements a text classification method on classifying a blog as joy, angry, sad or fear using a simple unsupervised learning algorithm. The classification of a blog text is predicted by the max semantic orientation (SO) of the phrases in the blog text that contains adjectives or adverbs. In this paper, the SO of a phrase is calculated as the mutual information between the given phrase and the polar words. Then the SO of the given blog text is determined by the max mutual information value. A blog text is classified as joy if the SO of its phrases is joy. Two different corpora are adopted to test our method, one is the Blog corpus collected by Monitor and Research Center for National Language Resource Network Multimedia Sub-branch Center, and the other is Chinese dataset provided by COAE2008 task. Based on the two datasets, the method respectively achieves a high improvement compared to the traditional methods.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116011509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4