2017 International Conference on Asian Language Processing (IALP)最新文献_第8页

Corpus for the legal information processing system (CLIPS): A Chinese legal corpus annotated with discourse information 法律信息处理系统语料库(CLIPS):一个带有话语信息注释的中文法律语料库

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300536

Hong Wang, Yunfeng Ge

引用次数: 0

Information entropy-informed sentence representation for question classification 基于信息熵的问题分类句子表示

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300550

Jingyang Gao, Miao Li, Lei Chen, Jinhua Du, R. Ma

引用次数: 0

Exploring semantic content to user profiling for user cluster-based collaborative point-of-interest recommender system 探索基于用户集群的协同兴趣点推荐系统的语义内容到用户分析

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300595

Yuhuan Xiu, Man Lan, Yuanbin Wu, Jun Lang

{"title":"Exploring semantic content to user profiling for user cluster-based collaborative point-of-interest recommender system","authors":"Yuhuan Xiu, Man Lan, Yuanbin Wu, Jun Lang","doi":"10.1109/IALP.2017.8300595","DOIUrl":"https://doi.org/10.1109/IALP.2017.8300595","url":null,"abstract":"Personalized recommender systems have become increasingly popular in recent years, as they have the ability to make appropriate choices for each active user. Collaborative filtering (CF) is the most successful and widely used technique in recommender systems, which aims at discovering similar users or items based on the history user rating records, i.e., user-item matrix. However, CF may not generate good recommendations when user-item matrix is very sparse. To address this problem, we explore the property category and semantic content to reduce the amount of items, which lead to more accurate performance when estimating user similarity. In addition, since the amount of users is quite huge, we first profile similar users with the aid of clustering algorithm before recommendation. Then, for each active user, the CF recommender system returns top recommendations from the narrow-down cluster the same as the active user by calculating user similarity with the help of item semantic information. The experiments have been performed on the benchmark dataset in NLPCC 2017 to recommend point-of-interest (POI) for each active user. The comparative results demonstrate that our proposed model outperforms the two baselines (i.e., a user-based CF system and an item-based CF system).","PeriodicalId":183586,"journal":{"name":"2017 International Conference on Asian Language Processing (IALP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122170629","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

Transfer learning for children's speech recognition 儿童语音识别的迁移学习

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300540

R. Tong, Lei Wang, B. Ma

{"title":"Transfer learning for children's speech recognition","authors":"R. Tong, Lei Wang, B. Ma","doi":"10.1109/IALP.2017.8300540","DOIUrl":"https://doi.org/10.1109/IALP.2017.8300540","url":null,"abstract":"Children's speech processing is more challenging than that of adults due to lacking of large scale children's speech corpora. With the developing of the physical speech organ, high inter speaker and intra speaker variabilities are observed in children's speech. On the other hand, data collection on children is difficult as children usually have short attention span and their language proficiency is limited. In this paper, we propose to improve children's automatic speech recognition performance with transfer learning technique. We compare two transfer learning approaches in enhancing children's speech recognition performance with adults' data. The first method is to perform acoustic model adaptation on the pre-trained adult model. The second is to train acoustic model with deep neural network based multi-task learning approach: the adults' and children's acoustic characteristics are learnt jointly in the shared hidden layers, while the output layers are optimized with different speaker groups. Our experiment results show that both transfer learning approaches are effective in transferring rich phonetic and acoustic information from adults' model to children model. The multi-task learning approach outperforms the acoustic adaptation approach. We further show that the speakers' acoustic characteristics in languages can also benefit the target language under the multi-task learning framework.","PeriodicalId":183586,"journal":{"name":"2017 International Conference on Asian Language Processing (IALP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115934204","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: 25

“nee intention enti?” towards dialog act recognition in code-mixed conversations “有意向吗?”的对话行为识别

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300589

Divya Sai Jitta, Khyathi Raghavi Chandu, Harsha Pamidipalli, R. Mamidi

{"title":"“nee intention enti?” towards dialog act recognition in code-mixed conversations","authors":"Divya Sai Jitta, Khyathi Raghavi Chandu, Harsha Pamidipalli, R. Mamidi","doi":"10.1109/IALP.2017.8300589","DOIUrl":"https://doi.org/10.1109/IALP.2017.8300589","url":null,"abstract":"Code-Mixing (CM) is a very commonly observed mode of communication in a multilingual configuration. The trends of using this newly emerging language has its effect as a culling option especially in platforms like social media. This becomes particularly important in the context of technology and health, where expressing the upcoming advancements is difficult in native language. Despite the change of such language dynamics, current dialog systems cannot handle a switch between languages across sentences and mixing within a sentence. Everyday conversations are fabricated in this mixed language and analyzing dialog acts in this language is very essential in further advancements of making interaction with personal assistants more natural. The problem is further compounded with crossing the script barriers in code-mixing. In this paper we take the first step towards understanding code-mixing in dialog processing, by recognizing dialog act (intention) of the code-mixed utterance. Considering the dearth of resources in code-mixed languages, we design our current system using only wordlevel resources such as language identification, transliteration and lexical translation. Our best performing system is HMM based with an F-score of 76.67.","PeriodicalId":183586,"journal":{"name":"2017 International Conference on Asian Language Processing (IALP)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129878463","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

Experimental research of mandarin diphthongs produced by uyghur learners 维吾尔语学习者普通话双元音的实验研究

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300546

Yultuz Rapkat, Glnur Arkin, A. Hamdulla

引用次数: 1

Mining Tibetan-Chinese bilingual entities from wikipedia 从维基百科中挖掘藏汉双语实体

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300534

Tao Jiang, Hongzhi Yu, Xiangzhen He, Xianghe Meng

引用次数: 1

Domain independent keyword identification for question answering 面向问答的领域独立关键字识别

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300554

Prathyusha Jwalapuram, R. Mamidi

引用次数: 1

Using topic analysis techniques to support comprehensive research paper searches 使用主题分析技术来支持全面的研究论文搜索

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300606

S. Fukuda, Yoichi Tomiura

{"title":"Using topic analysis techniques to support comprehensive research paper searches","authors":"S. Fukuda, Yoichi Tomiura","doi":"10.1109/IALP.2017.8300606","DOIUrl":"https://doi.org/10.1109/IALP.2017.8300606","url":null,"abstract":"In an academic paper search to confirm the originality of a user's research, it is important that the search returns comprehensive results relevant to the user's information need. To achieve comprehensive search results, users often relax initially restrictive search formula by adding synonyms and expressions similar to the search words with operator OR, and/or replacing AND with OR operations. However, it is difficult to anticipate all the terms that authors of relevant papers might have used. In addition, the replacement of AND with OR in search phrases can return a large number of unrelated papers. To overcome these issues, we propose a research paper search method based on topic analysis, which uses Boolean search based on the topics assigned to the search words in the search formula and the abstracts that contain any search word. Our method considers synonyms and expressions similar to the search words, which a user might not anticipate, while limiting the number of papers unrelated to the information need in the search result. To investigate the effectiveness of our method, we conducted experiments using the NTCIR-1 and 2 datasets, and confirmed that our method shows a reduction effect on unrelated papers, while maintaining high coverage.","PeriodicalId":183586,"journal":{"name":"2017 International Conference on Asian Language Processing (IALP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133352852","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 rule and statistical modeling based stem extraction method for kazakh words 基于规则和统计建模的哈萨克语词干提取方法

2017 International Conference on Asian Language Processing (IALP) Pub Date : 2017-12-01 DOI: 10.1109/IALP.2017.8300586

Rehmutulla Memet, Mewlude Nijat, Gulnigar Mahmut, A. Hamdulla

引用次数: 1