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2015 International Conference on Asian Language Processing (IALP)最新文献

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Performance scoring of singing voice 演唱声音的表演评分
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451546
Yang Yu, Weisi Lin, Dong-Yan Huang, M. Dong, Haizhou Li
{"title":"Performance scoring of singing voice","authors":"Yang Yu, Weisi Lin, Dong-Yan Huang, M. Dong, Haizhou Li","doi":"10.1109/IALP.2015.7451546","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451546","url":null,"abstract":"Singing voice offers rich information such as human emotions and moods, it is considered to be a particular musical instrument. Nowadays, there are many situations where the singing voice needs to be evaluated, such as teaching, singing competition, and so on. But not everyone has a professional teacher, a singing evaluation system will be very helpful for ordinary people to learn singing in a proper way. In this paper, a system is developed to analyze the performance of singing voice and rank it according to predictive model trained from the acoustic emotion features and musicians' opinions.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133038630","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: 3
The expression of singing emotion - contradicting the constraints of song 歌唱情感的表达——与歌曲的约束相矛盾
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451541
Gillian Chua, Qian Ci Chang, Ye Won Park, P. Chan, M. Dong, Haizhou Li
{"title":"The expression of singing emotion - contradicting the constraints of song","authors":"Gillian Chua, Qian Ci Chang, Ye Won Park, P. Chan, M. Dong, Haizhou Li","doi":"10.1109/IALP.2015.7451541","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451541","url":null,"abstract":"In speech, emotion is freely carried in the fundamental frequency, rate of speech, intensity and spectra of the human voice, although the spectra is largely dictated by words in speech. In singing, however, fundamental frequency and rhythm are constrained by the melody of the song, while the spectra is constrained by the song lyrics. Nevertheless, a large amount of emotion is carried in song; and the same song, with the same melody and rhythm constraints, may be expressed in a variety of emotions. This paper investigates the manner by which different emotions may be conveyed in the human singing voice, given the constraints of song. It goes further to find which subtle variations correspond to which emotion.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131830671","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: 3
Automatic segmentation of Chinese Mandarin speech into syllable-like 汉语普通话语音自动分词成音节
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451531
Jian Li, S. Furao
{"title":"Automatic segmentation of Chinese Mandarin speech into syllable-like","authors":"Jian Li, S. Furao","doi":"10.1109/IALP.2015.7451531","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451531","url":null,"abstract":"In this paper, we propose a novel approach to automatically segment a continuous Mandarin speech into syllable-like units. The main idea of our algorithm is to merge two round distinct selected boundaries using feature information generated from time and frequency domain. The first round segmentation is mainly based on aggregating the characteristics of different frequency regions and the second round employees zero crossing rate to improve the accuracy of segment results. The experimental results indicate that our hybrid method has high accuracy and coverage with respect to the reference boundaries even in low error tolerance.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121908153","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
Improving person name recognition quality in Chinese text with reinforced processing of ambiguities 加强歧义处理提高中文文本人名识别质量
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451556
Shuangyong Song, Zhongguang Zheng, Yao Meng
{"title":"Improving person name recognition quality in Chinese text with reinforced processing of ambiguities","authors":"Shuangyong Song, Zhongguang Zheng, Yao Meng","doi":"10.1109/IALP.2015.7451556","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451556","url":null,"abstract":"In this paper, we focus on the task of person name recognition (PNR) in Chinese text, which is an important part of Named entity recognition (NER). Chinese word segmentation makes the sequence tagging of PNR more accurate than character-based PNR, but it also brings more word-level ambiguities. For reducing the negative effect of word segmentation for PNR, we reinforce the analysis of ambiguities and propose a model to deal with them. Experimental results on People's Daily corpus show that the proposed model is effective in PNR.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122595574","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: 0
Attribute knowledge mining for Chinese word sense disambiguation 中文词义消歧的属性知识挖掘
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451535
Jianyong Duan, Yao Fu, xia li
{"title":"Attribute knowledge mining for Chinese word sense disambiguation","authors":"Jianyong Duan, Yao Fu, xia li","doi":"10.1109/IALP.2015.7451535","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451535","url":null,"abstract":"Word sense disambiguation is a technology of judging the specific semantic of polysemous words in the specific context. It is meaningful for the applications of natural language processing. This paper introduces the attribute knowledge into word sense disambiguation task. Every sense of the polysemous words can be described by the different attribute sets. These attributes can be viewed as a kind of context features. The attribute knowledge bases are built for every polysemous word, and employed into the Naive Bayes classifier and Maximum Entropy classifier as a dimension feature to judge the specific semantic of polysemous words in the specific context. The experimental results show that this method can effectively improve the accuracy of Chinese word sense disambiguation.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121022232","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
Effect of word segmentation on Arabic text classification 分词对阿拉伯语文本分类的影响
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451548
A. Al-Thubaity, A. Al-Subaie
{"title":"Effect of word segmentation on Arabic text classification","authors":"A. Al-Thubaity, A. Al-Subaie","doi":"10.1109/IALP.2015.7451548","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451548","url":null,"abstract":"The preprocessing stage in text classification is one of the factors affecting the accuracy of text classification. Text preprocessing involves several steps such as removing stop words, punctuation, and numerals. For Arabic text classification, stemming and root extraction were proposed as additional preprocessing steps. The resulting stems and roots are then used as features for Arabic text classification. In this study, we propose word segmentation as an additional preprocessing step. We used a dataset comprising 4,900 newspaper articles evenly distributed into seven classes. We conducted our experiments on segmented and non-segmented versions of this dataset. We used chi-squared to select top-ranked features, LTC as a representation schema, and SVM as a classifier. By measuring the accuracy, precision, recall, and F-measure, we evaluated the use of word orthography as a feature for Arabic text classification before and after segmentation. In all of the experiments we conducted, the classification performance for the segmented dataset outperformed the nonsegmented dataset with the same number of features. Furthermore, we can attain the same classification performance with nonsegmented datasets using fewer features.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"124 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120989503","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: 7
A hybrid method for sentiment classification in Chinese Movie Reviews based on sentiment labels 基于情感标签的中文影评情感分类混合方法
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451538
Kai Zhao, Yaohong Jin
{"title":"A hybrid method for sentiment classification in Chinese Movie Reviews based on sentiment labels","authors":"Kai Zhao, Yaohong Jin","doi":"10.1109/IALP.2015.7451538","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451538","url":null,"abstract":"This paper proposes a method of sentiment classification in Chinese movie reviews. Given a Chinese Movie Review, we classify its sentiment as positive, neutral or negative. We introduce a hybrid approach based on sentiment labels which combining semantic based method with Support Vector Machine(SVM) machine learning method. We regard each review text as a sentiment phrases sequence, the approach first obtains two potential sentiment labels for each Chinese movie review by using semantic based and machine learning based approach respectively, and then regards hybrid labels as new features for machine learning based classification to improve its performance. Experimental results using hybrid method based on sentiment labels show the effectiveness and superior performance of the proposed approach.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115406966","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: 7
Recognizing entailment in Chinese texts with feature combination 基于特征组合的中文文本蕴涵识别
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451537
Maofu Liu, Yifan Guo, Liqiang Nie
{"title":"Recognizing entailment in Chinese texts with feature combination","authors":"Maofu Liu, Yifan Guo, Liqiang Nie","doi":"10.1109/IALP.2015.7451537","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451537","url":null,"abstract":"In recent years, the natural language processing community has been manifesting increasing interest in textual entailment recognition among English texts. Yet, so far, not much attention has been paid to textual entailment recognition in Chinese texts. Recognizing entailment can be cast as a classification problem, and in this paper, a classification model based on support vector machine is constructed to detect semantic relations in Chinese text pair, including forward entailment, reverse entailment, bidirectional entailment, contradiction and independence for the multi-class task. We introduce different feature combinations based on four kinds of features, containing Chinese surface textual, Chinese lexical semantic, Chinese syntactic and Chinese linguistic phenomena features, to our classification model. The experimental results on NTCIR RITE-3 data collection show that the accuracy of our classification model using the feature combination with all the four kinds of Chinese textual features achieves a much better performance than all other systems on multi-class task.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127460560","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: 2
A novel method to optimize training data for translation model adaptation 一种新的翻译模型自适应训练数据优化方法
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451517
Hao Liu, Yu Hong, Liang Yao, Le Liu, Jianmin Yao, Qiaoming Zhu
{"title":"A novel method to optimize training data for translation model adaptation","authors":"Hao Liu, Yu Hong, Liang Yao, Le Liu, Jianmin Yao, Qiaoming Zhu","doi":"10.1109/IALP.2015.7451517","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451517","url":null,"abstract":"In this paper, we explore the method to improve the cross-domain adaptation of current translation models, with the aim to solve the common problem that ambiguous linguistic knowledge in different domain causes a difficult training for a robust translation model. Specially, we propose a novel method to automatically optimize training data for translation model adaptation. The method combines a test sentence and its best candidate translation to generate a pseudo-parallel translation pair. Regarding the pairs as queries, the method follows a twin-track retrieval approach to further mine parallel sentence pairs from large-scale bilingual resources. Experiments show that by using our method, the optimized translation models significantly improve the translation performance by 1.8 BLEU points when only 7.7% of bilingual training data is used.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843182","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: 0
Extracting coordinate word pairs for dependency parsing 提取坐标词对以进行依赖项解析
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451536
Junjie Yu, Wenliang Chen
{"title":"Extracting coordinate word pairs for dependency parsing","authors":"Junjie Yu, Wenliang Chen","doi":"10.1109/IALP.2015.7451536","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451536","url":null,"abstract":"The subtask of identifying coordinate structures in Chinese dependency analysis is a challenging problem. The accuracy of coordinate word recognition remains below the average. To address this problem, we propose an automatic identification method based on large-scale unlabeled corpus. We then integrate a set of new features corresponding to the collected word pairs into the dependency parser. Specifically, our proposed method is based on the presence of easy-to-identify coordinate fragments. Our method can be divided into two steps. In the first step, we leverage two hand-crafted rules to extract highly accurate coordinate word pairs as seed words. The second step is to utilize seed words to extract coordinate structures in the corpus for further use of coordinate word pair extraction. Experimental results show that the extracted coordinate word pairs can significantly improve the accuracy on coordinate structure dependency analysis.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126014837","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: 1
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