2019 International Conference on Asian Language Processing (IALP)最新文献_第6页

Coarse-to-Fine Document Ranking for Multi-Document Reading Comprehension with Answer-Completion 基于答案补全的多文档阅读理解的从粗到精排序

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037670

Hongyu Liu, Shumin Shi, Heyan Huang

引用次数: 0

CIEA: A Corpus for Chinese Implicit Emotion Analysis 汉语内隐情绪分析语料库

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037667

Dawei Li, Jin Wang, Xuejie Zhang

引用次数: 0

Improved DNN-HMM English Acoustic Model Specially For Phonotactic Language Recognition 专为语音识别而改进的DNN-HMM英语声学模型

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037696

Weiwei Liu, Ying Yin, Ya-Nan Li, Yu-Bin Huang, Ting Ruan, Wei Liu, Rui-Li Du, Hua Bai, Wei Li, Sheng-Ge Zhang, Guo-Chun Li, Cun-Xue Zhang, Hai-Feng Yan, Jing He, Ying-Xin Gan, Yan-Miao Song, Jianhua Zhou, Jian-zhong Liu

{"title":"Improved DNN-HMM English Acoustic Model Specially For Phonotactic Language Recognition","authors":"Weiwei Liu, Ying Yin, Ya-Nan Li, Yu-Bin Huang, Ting Ruan, Wei Liu, Rui-Li Du, Hua Bai, Wei Li, Sheng-Ge Zhang, Guo-Chun Li, Cun-Xue Zhang, Hai-Feng Yan, Jing He, Ying-Xin Gan, Yan-Miao Song, Jianhua Zhou, Jian-zhong Liu","doi":"10.1109/IALP48816.2019.9037696","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037696","url":null,"abstract":"The now-acknowledged sensitive of Phonotactic Language Recognition (PLR) to the performance of the phone recognizer front-end have spawned interests to develop many methods to improve it. In this paper, improved Deep Neural Networks Hidden Markov Model (DNN-HMM) English acoustic model front-end specially for phonotactic language recognition is proposed, and series of methods like dictionary merging, phoneme splitting, phoneme clustering, state clustering and DNN-HMM acoustic modeling (DPPSD) are introduced to balance the generalization and the accusation of the speech tokenizing processing in PLR. Experiments are carried out on the database of National Institute of Standards and Technology language recognition evaluation 2009 (NIST LRE 2009). It is showed that the DPPSD English acoustic model based phonotactic language recognition system yields 2.09%, 6.60%, 19.72% for 30s, 10s, 3s in equal error rate (EER) by applying the state-of-the-art techniques, which outperforms the language recognition results on both TIMIT and CMU dictionary and other phoneme clustering methods.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126973808","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

Fusion of Image-text attention for Transformer-based Multimodal Machine Translation 基于变压器的多模态机器翻译的图像-文本注意融合

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037732

Junteng Ma, Shihao Qin, Lan Su, xia li, Lixian Xiao

引用次数: 1

Confidence Modeling for Neural Machine Translation 神经机器翻译的置信度建模

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037709

Taichi Aida, Kazuhide Yamamoto

{"title":"Confidence Modeling for Neural Machine Translation","authors":"Taichi Aida, Kazuhide Yamamoto","doi":"10.1109/IALP48816.2019.9037709","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037709","url":null,"abstract":"Current methods of neural machine translation output incorrect sentences together with sentences translated correctly. Consequently, users of neural machine translation algorithms do not have a way to check which outputted sentences have been translated correctly without employing an evaluation method. Therefore, we aim to define the confidence values in neural machine translation models. We suppose that setting a threshold to limit the confidence value would allow correctly translated sentences to exceed the threshold; thus, only clearly translated sentences would be outputted. Hence, users of such a translation tool can obtain a particular level of confidence in the translation correctness. We propose some indices; sentence log-likelihood, minimum variance, and average variance. After that, we calculated the correlation between each index and bilingual evaluation score (BLEU) to investigate the appropriateness of the defined confidence indices. As a result, sentence log-likelihood and average variance calculated by probability have a weak correlation with the BLEU score. Furthermore, when we set each index as the threshold value, we could obtain high quality translated sentences instead of outputting all translated sentences which include a wide range of quality sentences like previous work.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130839368","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

Research on New Event Detection Methods for Mongolian News 蒙文新闻事件检测新方法研究

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037708

Shijie Wang, F. Bao, Guanglai Gao

引用次数: 2

The Initial Research of Mongolian Literary Corpus-Take the Text of Da.Nachugdorji’s Work for Instance 蒙古族文学语料库初探——以《达》文本为例。比如纳丘多吉的作品

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037660

Yin Hai

引用次数: 0

Articulatory Features Based TDNN Model for Spoken Language Recognition 基于发音特征的TDNN模型用于口语识别

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037566

Jiawei Yu, Minghao Guo, Yanlu Xie, Jinsong Zhang

引用次数: 4

A Multi-stage Strategy for Chinese Discourse Tree Construction 汉语语篇树构建的多阶段策略

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037684

Tishuang Wang, Peifeng Li, Qiaoming Zhu

引用次数: 0

Automatic Meta-evaluation of Low-Resource Machine Translation Evaluation Metrics 低资源机器翻译评价指标的自动元评价

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037658

Junting Yu, Wuying Liu, Hongye He, Lin Wang

{"title":"Automatic Meta-evaluation of Low-Resource Machine Translation Evaluation Metrics","authors":"Junting Yu, Wuying Liu, Hongye He, Lin Wang","doi":"10.1109/IALP48816.2019.9037658","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037658","url":null,"abstract":"Meta-evaluation is a method to assess machine translation (MT) evaluation metrics according to certain theories and standards. This paper addresses an automatic meta-evaluation method of machine translation evaluation based on ORANGE- Limited ORANGE, which is applied in low-resource machine translation evaluation. It is adopted when the resources are limited. And take the three n-gram-based metrics - BLEUS, ROUGE-L and ROUGE-S for experiment, which is called horizontal comparison. Also, vertical comparison is used to compare the different forms of the same evaluation metric. Compared with the traditional human method, this method can evaluate metrics automatically without extra human involvement except for a set of references. It only needs the average rank of the references, and will not be influenced by the subjective factors. And it costs less and expends less time than the traditional one. It is good for the machine translation system parameter optimization and shortens the system development period. In this paper, we use this automatic meta-evaluation method to evaluate BLEUS, ROUGE-L, ROUGE-S and their different forms based on Cilin on the Russian-Chinese dataset. The result shows the same as that of the traditional human meta-evaluation. In this way, the consistency and effectiveness of Limited ORANGE are verified.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123026184","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