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"Speech Emotion Recognition from Social Media Voice Messages Recorded in the Wild"

Lucía Gómez-Zaragozá, Javier Marín-Morales, Elena Parra, Jaime Guixeres, Mariano Alcañiz
<span title="2020-07-07">2020</span> <i title="Zenodo"> Zenodo </i> &nbsp;
As a result, a great amount of voice data is generated every day, representing a new challenging approach for speech emotion recognition in real environments.  ...  Speech is the most natural way for human communication, carrying the emotional state of the speaker that plays an important role in social interaction.  ...  Speech Emotion Recognition from Social Media Voice Messages Recorded  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4018575">doi:10.5281/zenodo.4018575</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aroqhgoc2ncl7depljnocqyg7e">fatcat:aroqhgoc2ncl7depljnocqyg7e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200918221931/https://zenodo.org/record/4018575/files/HCI2020_speech_recognition.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.4018575"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Automating annotation of information-giving for analysis of clinical conversation

Elijah Mayfield, M Barton Laws, Ira B Wilson, Carolyn Penstein Rosé
<span title="">2014</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/aapnwtybrvghlc35hfimbtdlom" style="color: black;">JAMIA Journal of the American Medical Informatics Association</a> </i> &nbsp;
We aggregated selected speech acts into information-giving and requesting, then trained the machine to automatically annotate using logistic regression classification.  ...  We aimed to show that through machine learning, computers could code certain categories of speech acts with sufficient reliability to make useful distinctions among clinical encounters.  ...  All machine learning techniques described in this work are essentially standard tools for using machine learning with text input.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1136/amiajnl-2013-001898">doi:10.1136/amiajnl-2013-001898</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/24029598">pmid:24029598</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3957397/">pmcid:PMC3957397</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x3wlvwengbfprawytens5ezwf4">fatcat:x3wlvwengbfprawytens5ezwf4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180728072523/https://watermark.silverchair.com/21-e1-e122.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAbAwggGsBgkqhkiG9w0BBwagggGdMIIBmQIBADCCAZIGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMZ3BwOEx4T-k6JnIVAgEQgIIBY91Q72xycoNsOeEeme6XGBCvfzw7bIonKTyO9OxzBPAVEDDs306d0u9QDMjI5hfNlWJx3BTA1aC0L7g6iHcDBA36iPRxQY8P9KnCyNUeN7jm6mHpL4UawYrYwytv-JMi4eOMECx1qUS2uK8TDKrNwvEgfHzrQWkFOwZh7fMImiHaoMot-aeNk7va6hIzVmPrC5CjQyX4mflasB9BHZRGf5QVn_dqTYjXjs-7VTSJny0EgJ-mfND1fb9DPpwTTIX3Svm-oOYLY9Hh1TE75teGwBDutw_oFMEy26NzEnoCjE0OHpwyf4MCx28-CsSyTUu3COc_sLzUutGGQFFcWg74E_5O0Ni2VJevf6BZGGu9sblUjAh8gztTcVhWFSWTXNcZeZHQHYBRl2aAx7ffV7I9cEzb5Ds8easS7IlvljHMWoZBFw00YpoYEeX_QWfB4-ar0z0-3CUdRL5f-UlCH5r4hT1DPPU" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/e8/31e81e3ee05cf0e6f0e02c2151b8ccd03669e3c2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1136/amiajnl-2013-001898"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3957397" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Arabic Speech Emotion Recognition from Saudi Dialect Corpus

Reem H. Aljuhani, Areej Alshutayri, Shahd Alahdal
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
The emotion classification models were conducted using Scikit-learn machine learning library version 0.24.1 [21] .  ...  SVM is a powerful and efficient machine learning algorithm that is used for classification and pattern recognition [11] . KNN is one of the most extensively used classifiers in SER systems [12] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3110992">doi:10.1109/access.2021.3110992</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/c73knoukoradles6fmny6sgffq">fatcat:c73knoukoradles6fmny6sgffq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210908120152/https://ieeexplore.ieee.org/ielx7/6287639/6514899/09530700.pdf?tp=&amp;arnumber=9530700&amp;isnumber=6514899&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bc/cd/bccdf0c84c8e95f888c87aa53035af736bcd5679.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3110992"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

MACHINE LEARNING-THE FUTURE OF TECHNOLOGY

Anirban Chakraborty
<span title="2020-05-31">2020</span> <i title="IJEAST"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/namhphsg6rdvtofp27o3scimoy" style="color: black;">International Journal of Engineering Applied Sciences and Technology</a> </i> &nbsp;
Learning machine is a data analytical tool which automates the creation of the analytical model.  ...  Algorithms used for the machine learning submit data and based on that new results may be generated.  ...  (C) REINFORCEMENT LEARNING A learning algorithm or agent for strengthening learning learns from interacting with the surroundings.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33564/ijeast.2020.v05i01.132">doi:10.33564/ijeast.2020.v05i01.132</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jjcoyd3vsjfmzd74yt7l5zm33a">fatcat:jjcoyd3vsjfmzd74yt7l5zm33a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210814074237/https://www.ijeast.com/papers/754-756,Tesma501,IJEAST.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d0/9b/d09bff3e77801568734320604d308cbb8dbcc0cb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33564/ijeast.2020.v05i01.132"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Automatic hate speech detection in online contents using latent semantic analysis

Xhemal Zenuni, Jaumin Ajdari, Florije Ismaili, Bujar Raufi
<span title="2017-06-30">2017</span> <i title="Pressacademia"> Pressacademia </i> &nbsp;
A hate speech corpus for Albanian language is created, and then based on Support Vector Machine (SVM) approach, an automatic hate speech detection system is proposed.  ...  Therefore, we explore the idea of building of automatic classifier that can be used for detection of hate speech in public Albanian language pages.  ...  RtextTool is an easy to use tool that can be used for end-to-end implementation by interfacing with existing pre-processing routines and machine learning algorithms.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17261/pressacademia.2017.612">doi:10.17261/pressacademia.2017.612</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4fcli7gqpnfm3ciezhqlpcco6m">fatcat:4fcli7gqpnfm3ciezhqlpcco6m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180605063137/http://www.pressacademia.org/images/documents/procedia/archives/vol_5/050.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ce/ad/cead7cc11adcd66ab2f42ebe9c03b09844eca705.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.17261/pressacademia.2017.612"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Hate Speech Detection in Ethiopian Social Media Text

Arefat Hyeredin
<span title="2020-02-05">2020</span> <i title="Zenodo"> Zenodo </i> &nbsp;
This is a research proposal on hate speech detection in ethiopian social media text.  ...  Word Embedding: Deep learning techniques are recently being used in text classification and sentiment analysis with high accuracy.  ...  While social media provides an important avenue for communication and sharing, it also acts as a means of spreading hate speech online.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.3677486">doi:10.5281/zenodo.3677486</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vv7yykwklfal7j6ah2u3hptmbi">fatcat:vv7yykwklfal7j6ah2u3hptmbi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200811183619/https://zenodo.org/record/3677487/files/Research%20Proposal%20on%20Hate%20Speech%20Detection%20on%20Ethiopian%20Social%20Media%20Text%20using%20Sentiment%20Analysis.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/91/4e/914ef12fa94922f584c06241819a3e1daef691b7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.3677486"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Emotion Recognition In Persian Speech Using Deep Neural Networks [article]

Ali Yazdani, Hossein Simchi, Yaser Shekofteh
<span title="2022-04-28">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Speech Emotion Recognition (SER) is of great importance in Human-Computer Interaction (HCI), as it provides a deeper understanding of the situation and results in better interaction.  ...  Using signal features in low- and high-level descriptions and different deep networks and machine learning techniques, Unweighted Average Recall (UAR) of 65.20 is achieved with an accuracy of 78.29.  ...  The openSMILE tool provides various features for extracting speech files.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.13601v1">arXiv:2204.13601v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2vobdh6paffj3gmae7ecl6xpuq">fatcat:2vobdh6paffj3gmae7ecl6xpuq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220429013723/https://arxiv.org/ftp/arxiv/papers/2204/2204.13601.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/76/b8/76b896c4cac8d782f1fca1724dfcedc1aedde784.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.13601v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Supervised domain adaptation for emotion recognition from speech

Mohammed Abdelwahab, Carlos Busso
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rc5jnc4ldvhs3dswicq5wk3vsq" style="color: black;">2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</a> </i> &nbsp;
We address the following key questions in the context of supervised adaptation for speech emotion recognition: (a) how much labeled data is needed for adaptation to achieve good performance?  ...  We address these problems by using a multi-corpus framework where the models are trained and tested with different databases.  ...  Instead of collecting and annotating extra data when the target domain changes, many machine learning studies have proposed transfer learning schemes that use limited labeled data (supervised) or unlabeled  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2015.7178934">doi:10.1109/icassp.2015.7178934</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icassp/Abdel-WahabB15.html">dblp:conf/icassp/Abdel-WahabB15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/56aubyvwnfhvxkgzpw6hbyxs3y">fatcat:56aubyvwnfhvxkgzpw6hbyxs3y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809042338/http://ecs.utdallas.edu/research/researchlabs/msp-lab/publications/Abdelwahab_2015.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/91/fb/91fb6d80672f1e99a82cf127e9c1b94965556525.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2015.7178934"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Voice Recognition System Through Machine Learning

<span title="2019-08-10">2019</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cj3bm7tgcffurfop7xzswxuks4" style="color: black;">VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE</a> </i> &nbsp;
It is challenging task for a computer to understand and act according to human voice rather than to commands or programs.  ...  , then analyzing the text extracted from speech in the form of tokens through Machine Learning.  ...  This metric is used where output is a text string rather than being a classification. It is an algorithm for evaluating the performance of machine translation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijitee.j1072.0881019">doi:10.35940/ijitee.j1072.0881019</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gwyqvkuc6jdpjpuxfnqyonuniy">fatcat:gwyqvkuc6jdpjpuxfnqyonuniy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220122022057/https://www.ijitee.org/wp-content/uploads/papers/v8i10/J10720881019.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6b/c2/6bc2aa470e07ad6b2cd096e47ed2e21bbc9f0088.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijitee.j1072.0881019"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Natural Gas Price Prediction Using Machine Learning

Sanjana G P
<span title="2021-08-10">2021</span> <i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a> </i> &nbsp;
Here a new model for predicting price for natural gas by using Machine Learning concepts.  ...  There are plenty of methods for analyzing and forecasting natural gas prices and machine learning is increasingly used.  ...  At present, all commercial purpose speech recognition system uses a machine learning approach to recognize the speech.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2021.37291">doi:10.22214/ijraset.2021.37291</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/siin4sniyfdtjchdkewuxni4wa">fatcat:siin4sniyfdtjchdkewuxni4wa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210809022736/https://www.ijraset.com/fileserve.php?FID=37291" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/45/ac/45ac9cb9bd5b5e56680fef4de3af0c32d358640c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2021.37291"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Multimodal Fusion Algorithm and Reinforcement Learning-Based Dialog System in Human-Machine Interaction

Hanif Fakhrurroja, Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Indonesia, Carmadi Machbub, Ary Setijadi Prihatmanto, Ayu Purwarianti, Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Indonesia, Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Indonesia, Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Indonesia
<span title="2020-12-31">2020</span> <i title="School of Electrical Engineering and Informatics (STEI) ITB"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hx5jmhpxmbhyfkfotpecyehnom" style="color: black;">International Journal on Electrical Engineering and Informatics</a> </i> &nbsp;
This study developed a method of human-machine interaction system.  ...  These problems include how to design an interface system for a machine to contextualize the existing conversations.  ...  Multiclass proposes a DDAG strategy for classification using a binary classification model of 2 k(k-1) where k is the number of classes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15676/ijeei.2020.12.4.19">doi:10.15676/ijeei.2020.12.4.19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tun3mqo3a5cn7d5sui7bdd2o6y">fatcat:tun3mqo3a5cn7d5sui7bdd2o6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210204045855/http://ijeei.org/docs-6639471305fed2f0c0a487.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0d/b3/0db3585e706a3fe48fd956f43a4eeb3cb81b9d65.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15676/ijeei.2020.12.4.19"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGE

Zewdie Mossie, Jenq-Haur Wang
<span title="2018-06-28">2018</span> <i title="Figshare"> Figshare </i> &nbsp;
Authors employed Random forest and Naïve Bayes for learning and Word2Vec and TF-IDF for feature selection.  ...  The anonymity of social networks makes it attractive for hate speech to mask their criminal activities online posing a challenge to the world and in particular Ethiopia.  ...  The most common approach found in the work of [15] as a literature review consists in building a machine learning model for hate speech classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.6084/m9.figshare.6714884.v1">doi:10.6084/m9.figshare.6714884.v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yifu4maxsvbd3m4t2zmh2eafzq">fatcat:yifu4maxsvbd3m4t2zmh2eafzq</a> </span>
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Page 1358 of Linguistics and Language Behavior Abstracts: LLBA Vol. 28, Issue 3 [page]

<span title="">1994</span> <i > <a target="_blank" rel="noopener" href="https://archive.org/details/pub_linguistics-and-language-behavior-abstracts-llba" style="color: black;">Linguistics and Language Behavior Abstracts: LLBA </a> </i> &nbsp;
vision terminology, Ma-Ze entries; 9404910 finite state automata adaptations, natural language processing tools; 9405884 foreign-language learning/teaching, computer applications; 9404391 French as a  ...  Spanish as a for- eign language learners; 9406084 Italian basic vocabulary database structure/fields content; 9406100 machine translation systems, evaluation metrics review; 9405836 Middle High German  ... 
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Survey on AI-Based Multimodal Methods for Emotion Detection [chapter]

Catherine Marechal, Dariusz Mikołajewski, Krzysztof Tyburek, Piotr Prokopowicz, Lamine Bougueroua, Corinne Ancourt, Katarzyna Węgrzyn-Wolska
<span title="">2019</span> <i title="Springer New York"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6v4flwr6afbfrmhdyu6xe3dyvm" style="color: black;">Msphere</a> </i> &nbsp;
Automatic emotion recognition constitutes one of the great challenges providing new tools for more objective and quicker diagnosis, communication and research.  ...  Quick and accurate emotion recognition may increase possibilities of computers, robots, and integrated environments to recognize human emotions, and response accordingly to them a social rules.  ...  between the features, • Support Vector Machine (SVM) -supervised learning models with associated learning algorithms analyzing data used for classification and regression analysis.  ... 
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A web crowdsourcing framework for transfer learning and personalized Speech Emotion Recognition

Nikolaos Vryzas, Lazaros Vrysis, Rigas Kotsakis, Charalampos Dimoulas
<span title="">2021</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vui6j5722zev3lcb7xtzdug5nq" style="color: black;">Machine Learning with Applications</a> </i> &nbsp;
In Section 2, related state-of-the-art research on Speech Emotion Recognition, Transfer Learning, and crowdsourcing strategies for machine learning problems is cited.  ...  The platform can be used for the creation of personalized emotional speech datasets for speaker-adaptive SER, following the transfer learning strategies that have been evaluated.  ...  ), and participation in behavioral experiments on the interaction of human and machine learning systems.  ... 
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