2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)最新文献_第4页

Acoustic and language models adaptation for Indonesian spontaneous speech recognition 印尼语自发语音识别的声学和语言模型适应

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335375

D. Lestari, Angela Irfani

{"title":"Acoustic and language models adaptation for Indonesian spontaneous speech recognition","authors":"D. Lestari, Angela Irfani","doi":"10.1109/ICAICTA.2015.7335375","DOIUrl":"https://doi.org/10.1109/ICAICTA.2015.7335375","url":null,"abstract":"Performance of Indonesian Automatic Speech Recognition is decreased significantly when recognizing spontaneous speech. Spontaneous speech has particular characteristics differ from read speech both in acoustic and language rule. In spontaneous speech, the pronunciation and expression of the speech varies depending on the speaker fluency and the topic. Disfluencies in speech disrupt a fluent sentence and more often violates the rule of the formal language. To improve Indonesian automatic speech recognizer to recognize spontaneous speech, several model enhancement methods was conducted by adding spontaneous data and retrain both acoustic model and language model using those data, by adapting the acoustic model based on the maximum likelihood linear regression and maximum a posteriori approach, and by adapting the language model employing the language model linear interpolation. Experimental results show all methods are effective in increasing the capability of the Indonesian automatic speech recognizer to recognize spontaneous data. However, all methods decreased the accuracy of read speech recognition. On average, retraining both acoustic and language models using combination of read and spontaneous data is more effective than conducting model adaptation. The absolute improvement of 28.34% accuracy is achieved after retraining both language model and acoustic model using combination of read data and spontaneous data.","PeriodicalId":319020,"journal":{"name":"2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130993441","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

Interactive fluid simulation based on material point method for mobile devices 基于物质点法的移动设备交互流体仿真

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335379

Dody Dharma, Afwarman Manaf

引用次数: 2

Event extraction on Indonesian news article using multiclass categorization 基于多类分类的印尼语新闻文章事件提取

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335365

M. L. Khodra

引用次数: 8

Energy efficient routing in cluster based wireless sensor networks 基于集群的无线传感器网络节能路由

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335374

Sounak Paul, Tapan Dey

引用次数: 2

Combining temporal and content aware features for microblog retrieval 结合时间和内容感知特征的微博检索

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335353

Abu Nowshed Chy, Md Zia Ullah, Masaki Aono

{"title":"Combining temporal and content aware features for microblog retrieval","authors":"Abu Nowshed Chy, Md Zia Ullah, Masaki Aono","doi":"10.1109/ICAICTA.2015.7335353","DOIUrl":"https://doi.org/10.1109/ICAICTA.2015.7335353","url":null,"abstract":"Microblog, especially Twitter, have become an integral part of our daily life for searching latest news and events information. Due to short length characteristics of tweets, only content-relevance based search result cannot satisfy user's information need. Recent research shows that considering temporal aspects in this regard improve the retrieval performance significantly. In this paper, we propose a method to re-rank the search result based on temporal features, account related features, and Twitter specific features along with textual features of tweets. We also applied a two stage query expansion technique to improve the relevancy of tweets. After automatic feature selection by using LASSO and elastic-net regularization; we applied random forest as a feature ranking method to estimate the importance of selected feature. Then, with that importance score, a weighted ranking model combines the features value to estimate the relevance score. We conducted our experiments based on the TREC Microblog 2011 and 2012 queries over the TREC Tweets2011 collection. Experimental result demonstrates the effectiveness of our method over the baseline in terms of precision@30 (P@30), mean average precision (MAP), and reciprocal-precision (R-Prec) metrics.","PeriodicalId":319020,"journal":{"name":"2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"470 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116413266","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

The bilateral denoising performance influence of window, spatial and radiometric variance 窗、空间和辐射方差对双边去噪性能的影响

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335350

V. Patanavijit

{"title":"The bilateral denoising performance influence of window, spatial and radiometric variance","authors":"V. Patanavijit","doi":"10.1109/ICAICTA.2015.7335350","DOIUrl":"https://doi.org/10.1109/ICAICTA.2015.7335350","url":null,"abstract":"In the research operation of Digital Signal Processing (DSP) and Digital Image Processing (DIP), one of the most essential obstacles is the image denoise algorithm by the reason of a very large demand of high quality noise-free images therefore there are many image denoise algorithms have been invented in the time of two decades. Bilateral filter is one of the most impressive and feasible algorithms, which is usually applied for denoise propose, but the performance of the Bilateral filter is substantially bank on three parameters: spatial variance, radiometric variance and window size. Consequently, this paper investigates the performance influence impact of spatial variance, radiometric variance, window size for the Bilateral Filter in the denoise propose. In the denoise experiment, Bilateral filter (BF) is applied on three noisy standard images under five Gaussian noise power levels and the best results in the PSNR prospective point of view from deniose algorithm is picked. Moreover, an optimal value of three parameters: spatial variance, radiometric variance, window size, which make the performance of Bilateral filter the highest PSNR, are extensively investigated for each types of tested images and each noise powers.","PeriodicalId":319020,"journal":{"name":"2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115974366","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: 18

Integration of Diesel Engine monitoring system and recommendation system 柴油机监控系统与推荐系统的集成

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335363

N. Maulidevi, M. Al-Hasan, M. L. Khodra

引用次数: 1

Lattice Boltzmann method for two-dimensional shallow water equations with CUDA 二维浅水方程的格子玻尔兹曼方法

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335362

Jittavat Suksumlarn, W. Suwannik, M. Maleewong

引用次数: 0

Effectiveness of social media text classification by utilizing the online news category 利用在线新闻类别对社交媒体文本进行分类的有效性

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335361

Phat Jotikabukkana, Virach Sornlertlamvanich, Okumura Manabu, C. Haruechaiyasak

引用次数: 5

SAE: Syntactic-based aspect and opinion extraction from product reviews SAE:从产品评论中提取基于语法的方面和意见

2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2015-08-01 DOI: 10.1109/ICAICTA.2015.7335371

W. Maharani, D. H. Widyantoro, M. L. Khodra

{"title":"SAE: Syntactic-based aspect and opinion extraction from product reviews","authors":"W. Maharani, D. H. Widyantoro, M. L. Khodra","doi":"10.1109/ICAICTA.2015.7335371","DOIUrl":"https://doi.org/10.1109/ICAICTA.2015.7335371","url":null,"abstract":"Aspect extraction is an important task in sentiment analysis to identify aspects in customer review products. Most existing works defines the pattern set manually or using heuristic approach. In this paper, we propose SAE, a Syntactical-based Aspect Extraction using decision tree and rule learning to generate the pattern set based on sequence labelling. We provide a comprehensive analysis of aspect extraction using pattern-based method and typed-dependency. The patterns will be used to identify and extract aspect term candidates in customer product review. First, we generate pattern set that identify aspect term candidates using decision tree and rule learning such as ID3, J48, Random Tree, Part and Prism, based on sequence labelling. The set of pattern is employed to produced aspect term candidates. We use a list of positive and negative opinion lexicon as aspect term candidates filtering. Finally, we combine the pattern-based method with typed dependency to remove irrelevant aspect term. The results showed that the combination of pattern-based and typed dependency can increase the performance. However, since our work is based on syntactic-based approach, it can be used to other domains, that is expected to include an unlimited domain datasets.","PeriodicalId":319020,"journal":{"name":"2015 2nd International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132404496","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: 10