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EEG-based emotion classification based on Bidirectional Long Short-Term Memory Network

Jinru Yang, Xiaofan Huang, Hongkai Wu, Xingtong Yang
2020 Procedia Computer Science  
Emotion recognition can be achieved by speech recognition, the judgment of limb movements, analysis of Electrooculogram (EOG) or capturing of facial expressions.  ...  Abstract Emotion recognition can be achieved by speech recognition, the judgment of limb movements, analysis of Electrooculogram (EOG) or capturing of facial expressions.  ...  Ultimately, thanks go to our parents who are our mentor and guardian from the very beginning in primary school.  ... 
doi:10.1016/j.procs.2020.06.117 fatcat:zavbulylcbefhalfk3pdxrw5vy

Speech Paralinguistic Approach for Detecting Dementia Using Gated Convolutional Neural Network

Mariana RODRIGUES MAKIUCHI, Tifani WARNITA, Nakamasa INOUE, Koichi SHINODA, Michitaka YOSHIMURA, Momoko KITAZAWA, Kei FUNAKI, Yoko EGUCHI, Taishiro KISHIMOTO
2021 IEICE transactions on information and systems  
We extract paralinguistic features for a short speech segment and use Gated Convolutional Neural Networks (GCNN) to classify it into dementia or healthy.  ...  In the PROMPT Database, our method yields the accuracy of 74.7% using 4 seconds of speech data and it improves to 80.8% when we use all the patient's speech data.  ...  Acknowledgements This work was supported by JST CREST [grant numbers JPMJCR1687, JPMJCR19F5]; JSPS KAKEN [grant number 16H02845], and the Japan Agency for Medical Research and Development (AMED) number  ... 
doi:10.1587/transinf.2020edp7196 fatcat:zqeihesaxbh5fc52n5zuiixtgu

Multimodal Depression Severity Prediction from medical bio-markers using Machine Learning Tools and Technologies [article]

Shivani Shimpi, Shyam Thombre, Snehal Reddy, Ritik Sharma, Srijan Singh
2020 arXiv   pre-print
The given approach attempts to detect, emphasize, and classify the features of a depressed person based on the low-level descriptors for verbal and visual features, and context of the language features  ...  Using behavioural cues to automate depression diagnosis and stage prediction in recent years has relatively increased.  ...  Acknowledgements We thank the University of Southern California for providing the Distress Analysis Interview Corpus -Wizard of Oz (DAIC-WOZ) dataset and the extended DAIC dataset.  ... 
arXiv:2009.05651v2 fatcat:sjrf66l3qrb7hh5o63nvrbnc7e

A Multitask Deep Learning Approach for User Depression Detection on Sina Weibo [article]

Yiding Wang, Zhenyi Wang, Chenghao Li, Yilin Zhang, Haizhou Wang
2020 arXiv   pre-print
By analyzing the user's text, social behavior, and posted pictures, ten statistical features are concluded and proposed.  ...  In the meantime, text-based word features are extracted using the popular pretrained model XLNet. Moreover, a novel deep neural network classification model, i.e.  ...  The user domain contains the user's gender, birthday, profile (a short text of the user's self-description), the number of followers, the number of followings, and the list of tweets.  ... 
arXiv:2008.11708v1 fatcat:cyyip7bczfchplskgpteyiijma

EMG-to-Speech: Direct Generation of Speech From Facial Electromyographic Signals

Matthias Janke, Lorenz Diener
2017 IEEE/ACM Transactions on Audio Speech and Language Processing  
iii related EMG-to-speech work, shows a relative improvement of 29 % with our best performing mapping approach.  ...  Ein Vergleich der resultierenden Ergebnisse unseres besten Systems mit verwandten EMG-to-Speech Ansätzen zeigt eine relative Verbesserung von 29 %.  ...  There are four units that are connected to the input: a block input, an input gate, output gate and a forget gate.  ... 
doi:10.1109/taslp.2017.2738568 fatcat:qcct6eiqhrgarmbj7gh7cfcxmq

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
Thus, the fusion of physical information and physiological signals can provide useful features of emotional states and lead to higher accuracy.  ...  Major breakthroughs have been made recently in the areas of affective computing (i.e., emotion recognition and sentiment analysis).  ...  captured by three bidirectional gated recurrent unit (biGRU) networks.  ... 
arXiv:2203.06935v3 fatcat:h4t3omkzjvcejn2kpvxns7n2qe

Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world

Stephen Grossberg
2013 Neural Networks  
Due to the complementary organization of the brain, ART does not describe many spatial and motor behaviors whose matching and learning laws differ from those of ART.  ...  for the planning and control of sequences of linguistic, spatial, and motor information; conscious speech percepts that are influenced by future context; auditory streaming in noise during source segregation  ...  Acknowledgment This research was supported in part by the SyNAPSE program of DARPA (HR0011-09-C-0001).  ... 
doi:10.1016/j.neunet.2012.09.017 pmid:23149242 fatcat:thllnkdjzfg6riattqfpytjroa

MONAH: Multi-Modal Narratives for Humans to analyze conversations [article]

Joshua Y. Kim, Greyson Y. Kim, Chunfeng Liu, Rafael A. Calvo, Silas C.R. Taylor, Kalina Yacef
2021 arXiv   pre-print
Our feature engineering contributions are two-fold: firstly, we identify the range of multimodal features relevant to detect rapport-building; secondly, we expand the range of multimodal annotations and  ...  This system uses a set of preprocessing rules to weave multimodal annotations into the verbatim transcripts and promote interpretability.  ...  Acknowledgments We acknowledge the Sydney Informatics Hub and the University of Sydney's high-performance computing cluster, Artemis, for providing the computing resources and Marriane Makahiya for supporting  ... 
arXiv:2101.07339v2 fatcat:tpurdglfivbjpjhl3u45muxs34

Machine and cognitive intelligence for human health: systematic review

Xieling Chen, Gary Cheng, Fu Lee Wang, Xiaohui Tao, Haoran Xie, Lingling Xu
2022 Brain Informatics  
This provides important insights into the effective use of Web intelligence to support informatics-enabled brain studies.  ...  modeling for clinical or biomedical text mining, artificial neural networks and logistic regression for prediction, and convolutional neural networks and support vector machines for monitoring and classification  ...  Specifically, a Web system [58] developed based on the Google Web Speech API and Microsoft Bing Speech API generated medical reports via automatic speech recognition.  ... 
doi:10.1186/s40708-022-00153-9 pmid:35150379 pmcid:PMC8840949 fatcat:whia7d7zyze5rd6susl54ozcqq

Acetylcholine Neuromodulation in Normal and Abnormal Learning and Memory: Vigilance Control in Waking, Sleep, Autism, Amnesia and Alzheimer's Disease

Stephen Grossberg
2017 Frontiers in Neural Circuits  
This article uses ART to propose and unify the explanation of diverse data about normal and abnormal modulation of learning and memory by acetylcholine (ACh).  ...  Sleep disruptions before and during Alzheimer's disease, and how they contribute to a vicious cycle of plaque formation in layers 3 and 5, are also clarified from this perspective.  ...  Chunk-mediated gating via the basal ganglia allows speech to be heard in the correct temporal order, even when what is consciously heard depends upon using future context LGN axons send collaterals into  ... 
doi:10.3389/fncir.2017.00082 pmid:29163063 pmcid:PMC5673653 fatcat:ktis36fxtngzdm5n74o7hlhdxu

Speech Perception and Spoken Word Recognition: Past and Present

Peter W. Jusczyk, Paul A. Luce
2002 Ear and Hearing  
spoken word recognition, and research on how infants acquire the capacity to perceive their native language.  ...  Our foci in this review fall on three principle topics: early work on the discrimination and categorization of speech sounds, more recent efforts to understand the processes and representations that subserve  ...  ACKNOWLEDGMENTS: Preparation of the present manuscript was supported by a Senior Scientist Award from NIMH (01490) and a Research Grant from NICHD (15795) to PWJ and a Research Grant from NIDCD  ... 
doi:10.1097/00003446-200202000-00002 pmid:11881915 fatcat:2tj5axvwnrglzo2hmijp3z27vq

Healthcare Techniques Through Deep Learning: Issues, Challenges and Opportunities

Dur-E-Maknoon Nisar, Rashid Amin, Noor-Ul-Huda Shah, Mohammed A. Al Ghamdi, Sultan H. Almotiri, Meshrif Alruily
2021 IEEE Access  
Speech is a primary method of communication, the deep learning methods used for speech recognition are Gaussian Mixture Models (GMMs).  ...  The M.Sc. degree in Internet, Computer, and System Security from Bradford University, United Kingdom, in 2006, and the Ph.D. degree in Wireless Security from Bradford University, United Kingdom.  ... 
doi:10.1109/access.2021.3095312 fatcat:3ddvsz5eozav7opv6vvanohcs4

Clinical information extraction applications: A literature review

Yanshan Wang, Liwei Wang, Majid Rastegar-Mojarad, Sungrim Moon, Feichen Shen, Naveed Afzal, Sijia Liu, Yuqun Zeng, Saeed Mehrabi, Sunghwan Sohn, Hongfang Liu
2018 Journal of Biomedical Informatics  
One critical component used to facilitate the secondary use of EHR data is the information extraction (IE) task, which automatically extracts and encodes clinical information from text.  ...  Background-With the rapid adoption of electronic health records (EHRs), it is desirable to harvest information and knowledge from EHRs to support automated systems at the point of care and to enable secondary  ...  Acknowledgments Funding This work was made possible by NIGMS R01GM102282, NCATS U01TR002062, NLM R01LM11934, and NIBIB R01EB19403.  ... 
doi:10.1016/j.jbi.2017.11.011 pmid:29162496 pmcid:PMC5771858 fatcat:ybh6msngznbvtkksckpcmz4bxe

Text-based Sentiment Analysis and Music Emotion Recognition [article]

Erion Çano
2018 arXiv   pre-print
Second, there are various uncertainties regarding the use of word embedding vectors: should they be generated from the same data set that is used to train the model or it is better to source them from  ...  There are however several problems that need to be solved for efficient use of deep neural networks on text mining and text polarity analysis.  ...  It insinuates the recognition of opinion-oriented language in texts and its separation from the objective language.  ... 
arXiv:1810.03031v1 fatcat:4vj4euwtxbghbjdev2gutcgjny

ICCIT 2020 Conference Proceedings [Front matter]

2020 2020 23rd International Conference on Computer and Information Technology (ICCIT)  
Bhavani Thuraisingham is the Founders Chair Professor of Computer Science and the  ...  Shamim Anower 16:15-16:30 289 Image to Bengali Caption Generation Using Deep CNN and Bidirectional Gated Recurrent Unit Al Momin Faruk, Hasan Al Faraby, Md. Muzahidul Azad, Md.  ...  Image to Bengali Caption Generation Using Deep CNN and Bidirectional Gated Recurrenet Unit Tonmoy Islam and Safial Islam Ayon.  ... 
doi:10.1109/iccit51783.2020.9392749 fatcat:pz3hf7rsmzbjpe6hxjlu5tmrfq
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