2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)最新文献

Development of Political QA Systems aimed at Assembly Minutes based on Abstractive Summarization 基于抽象摘要的会议纪要政治问答系统开发

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640248

Teruya Kawai, T. Akiba, S. Masuyama

引用次数: 0

Conversational Speech Emotion Recognition From Indonesian Spoken Language Using Recurrent Neural Network-Based Model 基于循环神经网络模型的印尼语会话语音情感识别

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640273

Aisyah Nurul Izzah Adma, D. Lestari

{"title":"Conversational Speech Emotion Recognition From Indonesian Spoken Language Using Recurrent Neural Network-Based Model","authors":"Aisyah Nurul Izzah Adma, D. Lestari","doi":"10.1109/ICAICTA53211.2021.9640273","DOIUrl":"https://doi.org/10.1109/ICAICTA53211.2021.9640273","url":null,"abstract":"To achieve natural human-computer interaction, emotional aspects are incorporated in its development. Existing speech emotion recognition studies in the Indonesian language consider utterances as independent entities, ignoring relations among the conversations' utterances. This paper presents the study of conversational speech emotion recognition in Indonesian. We build an RNN-based model that enables utterances to capture contextual information from their surroundings in the same conversation, thus aiding the emotion classifier. We also construct the conversational emotion corpus in the language from the podcast about life experiences to obtain natural emotion on its utterances. Our experiments employ the Long-Short Term Memory (LSTM) and Gated-Recurrent Unit (GRU) algorithms to model the emotion using acoustic and lexical features. Evaluation of the experiment result achieves an F-measure of 58.17% for six emotion classes and an F-measure of 72.52% for four emotion classes by fusing acoustic and lexical contextual features using the LSTM model.","PeriodicalId":217463,"journal":{"name":"2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122452734","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

Text Classification Using XLNet with Infomap Automatic Labeling Process 使用XLNet和Infomap自动标注过程进行文本分类

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640255

Triana Dewi Salma, G. Saptawati, Yanti Rusmawati

引用次数: 0

Designing an Engaging News Aggregator Application with Social Features and Gamification 设计一个具有社交功能和游戏化的引人入胜的新闻聚合应用程序

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640252

Gardahadi Gardiadi, S.T. Ginar Santika Niwanputri

引用次数: 1

Hierarchical Semantic Segmentation Based Approach for Road Surface Damages and Markings Detection on Paved Road 基于层次语义分割的铺装道路路面损伤与标记检测方法

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640296

Fernao A. L. N. Mouzinho, Hidekazu Fukai

{"title":"Hierarchical Semantic Segmentation Based Approach for Road Surface Damages and Markings Detection on Paved Road","authors":"Fernao A. L. N. Mouzinho, Hidekazu Fukai","doi":"10.1109/ICAICTA53211.2021.9640296","DOIUrl":"https://doi.org/10.1109/ICAICTA53211.2021.9640296","url":null,"abstract":"Detection of road surface damages, such as potholes, cracks, and markings on a paved road from images captured by a dashcam is an essential issue in developing automatic road inspection systems. When we apply ordinary non-hierarchical semantic segmentation in this task, the system sometimes detects the potholes, cracks, and markings, outside the road area, e.g., in the sky, woods, etc. To address this issue, we propose a method to use a hierarchical structure on semantic segmentation. This method segments an input image in two levels of the layers. Firstly, the first level of the layer classifies the paved road and background. Next, the second level of the layer identifies potholes, cracks, and markings on a paved road area that is identified in the first level of the layer. To obtain a complete segmentation map, we apply the elementwise multiplication to the output of both levels of the layers. The U-Net was used in each semantic segmentation. We compared our method with ordinary non-hierarchical segmentation in terms of F1-score and Intersection over Union (IoU). Results show that our method outperforms the ordinary non-hierarchical segmentation for the overall classes in terms of F1-score and IoU. Compare to the ordinary non-hierarchical segmentation, our method improved the result; (i) from 76% to 85% of F1-score and 61% to 74% of IoU for potholes, (ii) from 62% to 68% of F1-score and 45% to 51% of IoU for cracks, (iii) from 89% to 90% of F1-score and 80% to 82% of IoU for markings.","PeriodicalId":217463,"journal":{"name":"2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116033779","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

Sadewa satellite remote sensing data to Manggarai 1-hour water level machine learning model Sadewa卫星遥感数据以Manggarai 1小时水位机器学习模型

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640254

Jonathan Raditya Valerian, F. Rohmat, H. Kardhana, M. Kusuma, M. Yatsrib

引用次数: 2

Humor Detection Using a Bidirectional Encoder Representations from Transformers (BERT) based Neural Ensemble Model 使用基于变压器双向编码器表征 (BERT) 的神经集合模型进行幽默检测

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640260

Rida Miraj, Masaki Aono

引用次数: 0

Improving the Performance of the Extractive Text Summarization by a Novel Topic Modeling and Sentence Embedding Technique using SBERT 基于SBERT的主题建模和句子嵌入技术提高抽取文本摘要的性能

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640295

Paulus Setiawan Suryadjaja, Rila Mandala

{"title":"Improving the Performance of the Extractive Text Summarization by a Novel Topic Modeling and Sentence Embedding Technique using SBERT","authors":"Paulus Setiawan Suryadjaja, Rila Mandala","doi":"10.1109/ICAICTA53211.2021.9640295","DOIUrl":"https://doi.org/10.1109/ICAICTA53211.2021.9640295","url":null,"abstract":"Given the limitations of human reading abilities and the massive amount of text data available in modern times, there is a need for an automatic text summarization system. One automatic text summarization method that produces a satisfactory summary is extractive text summarization based on density peaks clustering. Previous research that applied this method has become state-of-the-art for the DUC 2004 dataset. However, there is still an opportunity for further development, specifically by applying the artificial neural network-based sentence embedding technique to replace the embedding vector space model and LDA topic modeling that was previously used. This research proposes a cluster-based automatic text summarization system using Sentence-BERT (SBERT) to perform sentence embedding and topic modeling processes to improve the summarization technique proposed by previous research. SBERT was chosen because it has state-of-the-art performance on sentence embedding tasks, so it is expected to represent the semantic meaning of sentences better than the techniques used in previous studies. This research is the first research that applied SBERT for text summarization. This research also proposes several improvements for the sentence selection techniques used in previous studies. Based on the assessment using the ROUGE toolkit, the text summarization system built in this study succeeded in creating a better summary than the previous research.","PeriodicalId":217463,"journal":{"name":"2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127163824","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

Regression Models Analysis in Predicting the Impact of Population Growth on Flood Intensity in Jakarta 雅加达人口增长对洪水强度影响的回归模型分析

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640247

Michael Adriel Darmawan, Nathanael William Boentoro, Kevin Christian Surya, Derwin Suhartono

引用次数: 0

Tutorial System in Learning Activities Through Machine Learning-Based Chatbot Applications in Pharmacology Education 基于机器学习的聊天机器人在药理学教学中的应用

2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) Pub Date : 2021-09-29 DOI: 10.1109/ICAICTA53211.2021.9640275

M. R. Fonna, D. H. Widyantoro

{"title":"Tutorial System in Learning Activities Through Machine Learning-Based Chatbot Applications in Pharmacology Education","authors":"M. R. Fonna, D. H. Widyantoro","doi":"10.1109/ICAICTA53211.2021.9640275","DOIUrl":"https://doi.org/10.1109/ICAICTA53211.2021.9640275","url":null,"abstract":"Based on the education index issued by the United Nations Development Program and the Global Talent Competitiveness Index, education in Indonesia still needs to be improved through various innovations and infrastructure. One of them, the needs of students in the health sector (including in the field of pharmacology) to obtain learning information easily are still not widely implemented using information technology. Usually, students need to read textbooks and journals to get information that is in accordance with the lesson because there are not many materials about the health sector circulating on the internet, especially in the form of chatbots. One of the solutions that can overcome these problems is to utilize information technology through the use of chatbots in the field of pharmacology learning. In this research, a tutorial system for learning activities is built with a machine learning-based chatbot application. The general architecture of a chatbot consists of NLU components, message processor, dialogue management, action executor, and utterance generator. Based on evaluation, this research have successfully achieved 94.3% accuracy for intent classification and 97.5% accuracy for entity extraction. Majority of the users feel that the chatbot functionality is easy to use and easy to remember. Furthermore, majority of them (90%) thought that tutorial process provided by this chatbot is similar to the real tutorial process provided by human.","PeriodicalId":217463,"journal":{"name":"2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)","volume":"134 23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121416431","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