发布求助
文献互助 智能选刊 最新文献

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

筛选
英文 中文
Joint Chinese word segmentation and punctuation prediction using deep recurrent neural network for social media data 基于深度递归神经网络的中文分词和标点符号联合预测
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-24 DOI: 10.1109/IALP.2015.7451527
Kui Wu, Xuancong Wang, Nina Zhou, AiTi Aw, Haizhou Li
{"title":"Joint Chinese word segmentation and punctuation prediction using deep recurrent neural network for social media data","authors":"Kui Wu, Xuancong Wang, Nina Zhou, AiTi Aw, Haizhou Li","doi":"10.1109/IALP.2015.7451527","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451527","url":null,"abstract":"In this work, we propose to jointly perform Chinese word segmentation (CWS) and punctuation prediction (PU) in a unified framework using deep recurrent neural network (DRNN). We further perform a comparative study among the joint frameworks, the isolated prediction and the pipeline methods that link the two tasks sequentially, on a social media corpus. Our experimental results show that joint models improve performance of CWS and affect PU marginally. We also study the effects of CWS and PU on Chinese-to-English machine translation (MT) quality by evaluating on a parallel social media corpus. It is shown that joint models are superior to the isolated prediction and the pipeline approaches.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124142963","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
Context-extended phrase reordering model for pivot-based statistical machine translation 基于数据轴的统计机器翻译语境扩展短语重排模型
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451524
Xiaoning Zhu, T. Zhao, Yiming Cui, Conghui Zhu
{"title":"Context-extended phrase reordering model for pivot-based statistical machine translation","authors":"Xiaoning Zhu, T. Zhao, Yiming Cui, Conghui Zhu","doi":"10.1109/IALP.2015.7451524","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451524","url":null,"abstract":"For translation between language pairs which is lack of bilingual data, pivot-based SMT uses a pivot language as a “bridge” to generate source-target translation, inducing from source-pivot and pivot-target translation. However, due to the missing of the context information, the reordering model was hard to obtain with the conventional methods. In this paper, we present a context-extended phrase reordering model for pivot-based statistical machine translation by extending the context information in source, pivot and target language. Experimental results show that our method leads to significant improvements over the baseline system on European Parliament data.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"96 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":"131457243","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 bilingual multi-word expressions for low-resource statistical machine translation 面向低资源统计机器翻译的双语多词表达式提取
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451522
Linyu Wei, Miao Li, Lei Chen, Zhenxin Yang, Kai Sun, Man Yuan
{"title":"Extracting bilingual multi-word expressions for low-resource statistical machine translation","authors":"Linyu Wei, Miao Li, Lei Chen, Zhenxin Yang, Kai Sun, Man Yuan","doi":"10.1109/IALP.2015.7451522","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451522","url":null,"abstract":"Improving the performance of statistical machine translation is often a significant problem, especially in low language resource scenarios such as Chinese-Mongolian SMT. In this paper, we propose a method to improve the performance of Chinese-Mongolian SMT system using multi-word expressions, which is also a pilot study for this language pair. We extract MWEs from the phrase-table then integrate the MWEs into SMT system by various strategies. Experimental results indicate our method outperforms a baseline model by 0.81 BLEU points on Test-All and 1.54 BLEU points on Test-MWE.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"81 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":"115711657","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
Learning sentiment-inherent word embedding for word-level and sentence-level sentiment analysis 学习情感固有词嵌入，用于词级和句子级情感分析
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451540
Zhihua Zhang, Man Lan
{"title":"Learning sentiment-inherent word embedding for word-level and sentence-level sentiment analysis","authors":"Zhihua Zhang, Man Lan","doi":"10.1109/IALP.2015.7451540","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451540","url":null,"abstract":"Vector-based word representations have made great progress on many Natural Language Processing tasks. However, due to the lack of sentiment information, the traditional word vectors are insufficient to settle sentiment analysis tasks. In order to capture the sentiment information, we extended Continuous Skip-gram model (Skip-gram) and presented two sentiment word embedding models by integrating sentiment information into semantic word representations. Experimental results showed that the sentiment word embeddings learned by two models indeed capture sentiment and semantic information as well. Moreover, the proposed sentiment word embedding models outperform traditional word vectors on both Chinese and English corpora.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"16 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":"127676616","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: 19
Correlation analysis between social network content and query intention 社交网络内容与查询意图的相关性分析
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/ialp.2015.7451544
Jian Wang, Yu Hong, Kai Wang, Jianmin Yao, Qiaoming Zhu
{"title":"Correlation analysis between social network content and query intention","authors":"Jian Wang, Yu Hong, Kai Wang, Jianmin Yao, Qiaoming Zhu","doi":"10.1109/ialp.2015.7451544","DOIUrl":"https://doi.org/10.1109/ialp.2015.7451544","url":null,"abstract":"","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"117 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":"117339644","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
The annotation study of grammar points for TCSL 对外汉语语法点标注研究
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451534
Xiao-ru Tan, Lijiao Yang
{"title":"The annotation study of grammar points for TCSL","authors":"Xiao-ru Tan, Lijiao Yang","doi":"10.1109/IALP.2015.7451534","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451534","url":null,"abstract":"Corpus annotation is an important research subject in corpus linguistics, however, annotation research for teaching Chinese as a second language (TCSL) is scarce. It is difficult to retrieve data which are suitable for teaching from the general Chinese corpus. To deal with this problem, firstly, this paper proposed the concept of grammar points annotation and discussed the contents and methods of annotating grammar points in the corpus. Secondly, annotated 121 grammar points in 141464 sentences and got 95592 annotated data with semantic and syntactic information. Finally, this paper introduced the application of annotated data in TCSL.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"87 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":"127968074","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
Multi-view learning for emotion detection in code-switching texts 语码转换文本中情感检测的多视角学习
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451539
Sophia Yat-Mei Lee, Zhongqing Wang
{"title":"Multi-view learning for emotion detection in code-switching texts","authors":"Sophia Yat-Mei Lee, Zhongqing Wang","doi":"10.1109/IALP.2015.7451539","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451539","url":null,"abstract":"Previous researches have placed emphasis on analyzing emotions in monolingual text, neglecting the fact that emotions are often found in bilingual or code-switching posts in social media. Traditional methods for the identification or classification of emotion fail to accommodate the code-switching content. To address this challenge, in this paper, we propose a multi-view learning framework to learn and detect the emotions through both monolingual and bilingual views. In particular, the monolingual views are extracted from the monolingual text separately, and the bilingual view is constructed with both monolingual and translated text collectively. Empirical studies demonstrate the effectiveness of our proposed approach in detecting emotions in code-switching texts.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"89 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":"133361380","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: 11
Mandarin prosodic word prediction using dependency relationships 基于依赖关系的汉语韵律词预测
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451559
Zhengchen Zhang, Fuxiang Wu, M. Dong, Fu-qiu Zhou
{"title":"Mandarin prosodic word prediction using dependency relationships","authors":"Zhengchen Zhang, Fuxiang Wu, M. Dong, Fu-qiu Zhou","doi":"10.1109/IALP.2015.7451559","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451559","url":null,"abstract":"Previous research demonstrated that the dependency structure of a sentence is helpful for prosodic phrase boundary prediction in mandarin Text-To-Speech systems. However, no experimental results proved that the dependency relations are important to prosodic word boundary detection. Also, most of the published methods use machine learning technologies, which require people to label the prosodic boundaries manually for training purpose. In this paper, we propose a rule based method for prosodic word boundary prediction based on two observations. First, in most of the cases, a prosodic word is a lexical word, or it is a combination of adjacent lexical words. Second, the combination of lexical words relies on semantic relationships. The dependency tree of a sentence can describe the semantic relations between words. Hence, we combine adjacent words which have dependent relationships into a prosodic word. Some other restrictions are added to fine-tune the method. Experimental results demonstrate that the method achieved 0.918 and 0.901 on two corpora in terms of F-score.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"19 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":"121231498","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
A re-ranking model for dependency parsing with knowledge graph embeddings 基于知识图嵌入的依赖关系重新排序模型
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451560
A.-Yeong Kim, Hyun-Je Song, Seong-Bae Park, Sang-Jo Lee
{"title":"A re-ranking model for dependency parsing with knowledge graph embeddings","authors":"A.-Yeong Kim, Hyun-Je Song, Seong-Bae Park, Sang-Jo Lee","doi":"10.1109/IALP.2015.7451560","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451560","url":null,"abstract":"Re-ranking models of parse trees have been focused on re-ordering parse trees with a syntactic view. However, also a semantic view should be considered in re-ranking parse trees, because the fact that a word pair has a dependency implies that the pair has both syntactic and semantic relations. This paper proposes a re-ranking model for dependency parsing based on a combination of syntactic and semantic plausibilities of dependencies. The syntactic probability is used as a syntactic plausibility of a parse tree, and a knowledge graph embedding is adopted to represent its semantic plausibility. The knowledge graph embedding allows the semantic plausibility of parse trees to be expressed effectively with ease. The experiments on the standard Penn Treebank corpus prove that the proposed model improves the base parser regardless of the number of candidate parse trees.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"13 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":"115371194","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
Machine translation from Japanese and French to Vietnamese, the difference among language families 机器翻译从日语和法语到越南语，语族之间的差异
2015 International Conference on Asian Language Processing (IALP) Pub Date : 2015-10-01 DOI: 10.1109/IALP.2015.7451521
T. Do, M. Utiyama, E. Sumita
{"title":"Machine translation from Japanese and French to Vietnamese, the difference among language families","authors":"T. Do, M. Utiyama, E. Sumita","doi":"10.1109/IALP.2015.7451521","DOIUrl":"https://doi.org/10.1109/IALP.2015.7451521","url":null,"abstract":"Although Vietnamese is spoken language of more than 90 million people in the world (in 2014), Vietnamese language is still considered as a low-resourced language. Vietnamese NLP still lacks of resources for text and speech processing, especially research on machine translation for Vietnamese is very rare. This paper presents our first attempt to collect and construct French-Vietnamese and Japanese-Vietnamese statistical machine translation systems. These two different languages, French and Japanese, are less focused in Vietnamese-related machine translation research. The differences between these two languages in comparison with Vietnamese can bring out interesting observations.","PeriodicalId":256927,"journal":{"name":"2015 International Conference on Asian Language Processing (IALP)","volume":"129 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":"114471268","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
下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信