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Cross corpus multi-lingual speech emotion recognition using ensemble learning

Wisha Zehra, Abdul Rehman Javed, Zunera Jalil, Habib Ullah Khan, Thippa Reddy Gadekallu
2021 Complex & Intelligent Systems  
In this paper, a series of experiments are conducted to highlight an ensemble learning effect using a majority voting technique for cross-corpus, multi-lingual speech emotion recognition system.  ...  For cross-corpus experiments, an improvement of 2% when training on Urdu data and testing on German data and 15% when training on Urdu data and testing on Italian data is achieved.  ...  The proposed approach uses SVM with puk Kernel, complexity 1.0, and pairwise multi-class discrimination based on Sequential Minimal Optimization.  ... 
doi:10.1007/s40747-020-00250-4 fatcat:x7entb3govaztd4t442wtghskq

Sentiment/Subjectivity Analysis Survey for Languages other than English [article]

Mohammed Korayem, Khalifeh Aljadda, David Crandall
2016 arXiv   pre-print
The first (and the best) one is the language specific systems. The second type of systems involves reusing or transferring sentiment resources from English to the target language.  ...  The third type of methods is based on using language independent methods. The paper presents a separate section devoted to Arabic sentiment analysis.  ...  Different approaches for extracting the opinion holder in Arabic are proposed in [17] . Their approach is based on both pattern matching and machine learning.  ... 
arXiv:1601.00087v3 fatcat:zi4ikkge7ng4tfumhia4ytulwe

LiMoSINe Pipeline: Multilingual UIMA-based NLP Platform

Olga Uryupina, Barbara Plank, Gianni Barlacchi, Francisco J Valverde-Albacete, Manos Tsagkias, Antonio Uva, Alessandro Moschitti
2016 Proceedings of ACL-2016 System Demonstrations  
In particular, given an input text, the pipeline extracts: sentences and tokens; entity mentions; syntactic information; opinionated expressions; relations between entity mentions; co-reference chains  ...  We present a robust and efficient parallelizable multilingual UIMA-based platform for automatically annotating textual inputs with different layers of linguistic description, ranging from surface level  ...  Acknowledgements This work has been supported by the EU Projects FP7 LiMoSINe and H2020 5G-CogNet.  ... 
doi:10.18653/v1/p16-4027 dblp:conf/acl/UryupinaPBVTUM16 fatcat:tbxesxzcx5emxallenvvosjzyq

A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances [article]

Yan Wang, Wei Song, Wei Tao, Antonio Liotta, Dawei Yang, Xinlei Li, Shuyong Gao, Yixuan Sun, Weifeng Ge, Wei Zhang, Wenqiang Zhang
2022 arXiv   pre-print
Affective computing is realized based on unimodal or multimodal data, primarily consisting of physical information (e.g., textual, audio, and visual data) and physiological signals (e.g., EEG and ECG signals  ...  baseline dataset, fusion strategies for multimodal affective analysis, and unsupervised learning models.  ...  expression, and context-based learning provide important cues to better identify true affective states of the opinion holder [377, 378] .  ... 
arXiv:2203.06935v3 fatcat:h4t3omkzjvcejn2kpvxns7n2qe

Sentiment analysis using deep learning approaches: an overview

Olivier Habimana, Yuhua Li, Ruixuan Li, Xiwu Gu, Ge Yu
2019 Science China Information Sciences  
Moreover, based on knowledge learned from previous studies, the future work subsection shows the suggestions that can be incorporated into new deep learning models to yield better performance.  ...  Machine learning approaches are other traditional methods for sentiment analysis that are based on the machine learning algorithms to classify the words into their corresponding sentiment labels.  ...  Those tasks include opinion holder extraction and classification as well as time extraction and standardization.  ... 
doi:10.1007/s11432-018-9941-6 fatcat:nbevrfiyybhszirol2af26c6ve

Multi-class Twitter Data Categorization and Geocoding with a Novel Computing Framework [article]

Sakib Mahmud Khan, Mashrur Chowdhury, Linh B. Ngo, Amy Apon
2019 arXiv   pre-print
The analytical approach includes analyzing tweets using text classification and geocoding locations based on string similarity.  ...  Approximately 700,010 tweets are analyzed to extract relevant transportation-related information for one week.  ...  The model is implemented using Scikit-learn libraries. For the multi-class SVM problem, the one-vs-one decomposition process is used.  ... 
arXiv:1905.02916v3 fatcat:jf75ozjy7rbzliswdeaxl2kqgi

Multi-class twitter data categorization and geocoding with a novel computing framework

Sakib Mahmud Khan, Mashrur Chowdhury, Linh B. Ngo, Amy Apon
2020 Cities  
The analytical approach includes analyzing tweets using text classification and geocoding locations based on string similarity.  ...  Approximately 700,010 tweets are analyzed to extract relevant transportation-related information for one week.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the USDOT Center for Connected Multimodal Mobility  ... 
doi:10.1016/j.cities.2019.102410 fatcat:p5jppgfexfasfjwztezttagn5m

A Survey on Aspect-Based Sentiment Classification

Gianni Brauwers, Flavius Frasincar
2021 ACM Computing Surveys  
State-of-the-art ABSC models are discussed, such as models based on the transformer model, and hybrid deep learning models that incorporate knowledge bases.  ...  A novel taxonomy is proposed that categorizes the ABSC models into three major categories: knowledge-based, machine learning, and hybrid models.  ...  An alternative solution to the problem of a lack of data is the use of cross-lingual and multi-lingual models.  ... 
doi:10.1145/3503044 fatcat:hvd6gvhp6fgxtfavqarjsqv2g4

A Survey on Opinion Mining: from Stance to Product Aspect

Rui Wang, Deyu Zhou, Mingmin Jiang, Jiasheng Si, Yang Yang
2019 IEEE Access  
opinion mining based on the processing units and tasks.  ...  This survey focuses on two important subtasks in this field, stance detection and product aspect mining, both of which can be formalized as the problem of the triple target, aspect, opinion extraction.  ...  ACKNOWLEDGMENT We would like to thank the reviewers for their valuable comments and helpful suggestions.  ... 
doi:10.1109/access.2019.2906754 fatcat:5scny4gacvdivatd7m2lpky6ri

Deep Learning for Sentiment Analysis : A Survey [article]

Lei Zhang, Shuai Wang, Bing Liu
2018 arXiv   pre-print
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results.  ...  This paper first gives an overview of deep learning and then provides a comprehensive survey of its current applications in sentiment analysis.  ...  Acknowledgments Bing Liu and Shuai Wang's work was supported in part by National Science Foundation (NSF) under grant no. IIS1407927 and IIS-1650900, and by Huawei Technologies Co.  ... 
arXiv:1801.07883v2 fatcat:nplicfgaozb6fbfx4eyts4zt7e

Sentiment analysis and the complex natural language

Muhammad Taimoor Khan, Mehr Durrani, Armughan Ali, Irum Inayat, Shehzad Khalid, Kamran Habib Khan
2016 Complex Adaptive Systems Modeling  
Sentiment analysis (SA) extracts and aggregates users' sentiments towards a target entity.  ...  Machine learning (ML) techniques are frequently used as the natural language data is in abundance and has definite patterns.  ...  Acknowledgments We would like to thank Bahria University, Islambad for providing the necessary environment and support to carry out this work.  ... 
doi:10.1186/s40294-016-0016-9 fatcat:p53bqhtfsncltj6wzt5tyi3kyy

Emotionally Informed Hate Speech Detection: A Multi-target Perspective

Patricia Chiril, Endang Wahyu Pamungkas, Farah Benamara, Véronique Moriceau, Viviana Patti
2021 Cognitive Computation  
EmoSenticNet emotions, the first level emotions of SenticNet, a blend of SenticNet and EmoSenticNet emotions or affective features based on Hurtlex, obtained the best results.  ...  ), sexual orientation (homophobia), and so on.  ...  Pamungkas and Viviana Patti is partially funded by Progetto di Ateneo/CSP 2016 (Immigrants, Hate and Prejudice in Social Media, S1618.L2.BOSC.01) and by the project "Be Positive!"  ... 
doi:10.1007/s12559-021-09862-5 fatcat:742czn3qvnep5gt6hkaoccz75m

A survey on sentiment analysis in Urdu: A resource-poor language

Asad Khattak, Muhammad Zubair Asghar, Anam Saeed, Ibrahim A. Hameed, Syed Asif Hassan, Shakeel Ahmad
2020 Egyptian Informatics Journal  
Based on experimental results and proposals forwarded through this paper provides the groundwork for further studies on Urdu sentiment analysis. Ó 2020 THE AUTHORS.  ...  Background/introduction: The dawn of the internet opened the doors to the easy and widespread sharing of information on subject matters such as products, services, events and political opinions.  ...  This Research work was supported by Zayed University Research Incentives Fund#R18052, co-funded by Norwegian university of science and technology, Ålesund, Norway.  ... 
doi:10.1016/j.eij.2020.04.003 fatcat:qvymechpvnhypg2telxbs4wj4m

A Survey of Opinion Mining and Sentiment Analysis [chapter]

Bing Liu, Lei Zhang
2012 Mining Text Data  
However, finding and monitoring opinion sites on the Web and distilling the information contained in them remains a formidable task because of the proliferation of diverse sites.  ...  ., reviews, forum discussions, blogs and social networks) on the Web, individuals and organizations are increasingly using public opinions in these media for their decision making.  ...  Cross lingual opinion mining: This research involves opinion mining for a language corpus based on the corpora from other languages. It is needed in following scenarios.  ... 
doi:10.1007/978-1-4614-3223-4_13 fatcat:vpgpw7fvpzglfmla5w2x4wapwu

Spike-Timing-Dependent Plasticity [chapter]

2017 Encyclopedia of Machine Learning and Data Mining  
Aspect and Entity Extraction The task of aspect and entity extraction is to identify and extract opinion targets (aspect or entity) from opinion documents.  ...  The user often needs opinions from a large number of opinion holders, which leads to opinion summary.  ...  It is then possible to learn that to get box b to paris, the agent drives a truck to the city of b, loads box 1 on the truck, drives the truck to Paris, and finally unloads the box box 1 in Paris.  ... 
doi:10.1007/978-1-4899-7687-1_774 fatcat:2jprihjaxfbtpb3ttwuuz3u34y
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