Filters








741 Hits in 5.4 sec

Connecting Subspace Learning and Extreme Learning Machine in Speech Emotion Recognition

Xinzhou Xu, Jun Deng, Eduardo Coutinho, Chen Wu, Li Zhao, Bjorn W. Schuller
2018 IEEE transactions on multimedia  
Speech Emotion Recognition (SER) is a powerful tool for endowing computers with the capacity to process information about the affective states of users in human-machine interactions.  ...  In order to overcome these drawbacks, this paper leverages extreme learning machine for dimensionality reduction and proposes a novel framework to combine spectral regression based subspace learning and  ...  Extreme Learning Machines Recently, Extreme Learning Machines (ELMs) have been introduced as an alternative approach [21] - [26] for emotion recognition tasks [27] , [28] .  ... 
doi:10.1109/tmm.2018.2865834 fatcat:imkjnys55vhqdkpl6zoxqfmtdm

An Appraisal on Speech and Emotion Recognition Technologies based on Machine Learning

2020 International journal of recent technology and engineering  
But the idea of machine learning and various methods are necessary for the recognition of speech in the matter of interaction with machines.  ...  In this article, we attempted to explain a variety of speech and emotion recognition techniques and comparisons between several methods based on existing algorithms and mostly speech-based methods.  ...  In these, the trend-based and application-based publications are about vector machines for speech-based emotional recognition, age, gender, and speech-based speech recognition.  ... 
doi:10.35940/ijrte.e5715.018520 fatcat:6s2iovesz5bw5kzwer4s2ubaru

Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models

Babak Joze Abbaschian, Daniel Sierra-Sosa, Adel Elmaghraby
2021 Sensors  
The current study reviews deep learning approaches for SER with available datasets, followed by conventional machine learning techniques for speech emotion recognition.  ...  The advancements in neural networks and the on-demand need for accurate and near real-time Speech Emotion Recognition (SER) in human–computer interactions make it mandatory to compare available methods  ...  Emotion Recognition Using Deep Neural Network and Extreme Learning Machine, Han et al., 2014 [23] • DNN/3 • ANN/1 • ELM • MFCC • Delta MFCC • Pitch Period • Harmonics-To-Noise Ratio  ... 
doi:10.3390/s21041249 pmid:33578714 pmcid:PMC7916477 fatcat:nj5ihjhvnfcxtk7hu3n4zx4bka

Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition [article]

Shenglan Liu, Shuai Guo, Hong Qiao, Yang Wang, Bin Wang, Wenbo Luo, Mingming Zhang, Keye Zhang, Bixuan Du
2018 arXiv   pre-print
Human emotion recognition is an important direction in the field of biometric and information forensics. However, most existing human emotion research are based on the single RGB view.  ...  In this paper, we introduce a RGBD video-emotion dataset and a RGBD face-emotion dataset for research. To our best knowledge, this may be the first RGBD video-emotion dataset.  ...  Thanks for Shaohua Chen and Bin Zhan in the contribution of data acquisition of video-emotion dataset.  ... 
arXiv:1811.03478v1 fatcat:ylt5mmopvvhzva32dfhtyp2neq

Domain Regeneration for Cross-Database Micro-Expression Recognition

Yuan Zong, Wenming Zheng, Xiaohua Huang, Jingang Shi, Zhen Cui, Guoying Zhao
2018 IEEE Transactions on Image Processing  
In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases.  ...  Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.  ...  [30] proposed an importanceweighted support vector machine (IW-SVM) to handle crossdatabase speech emotion recognition.  ... 
doi:10.1109/tip.2018.2797479 pmid:29994602 fatcat:snus6rqb6vh2fkcz6yymqxcruq

A Review on Voice-based Interface for Human-Robot Interaction

Ameer Badr, Alia Abdul-Hassan
2020 Iraqi Journal for Electrical And Electronic Engineering  
With the recent developments of technology and the advances in artificial intelligence and machine learning techniques, it has become possible for the robot to understand and respond to voice as part of  ...  Numerous types of semantic understanding have been reviewed, such as speech recognition, speaker recognition, speaker gender detection, speaker gender and age estimation, and speaker localization.  ...  There are a lot of differences among human and machine speech production, but the increase in the ability of machine learning paradigms to simulate human speech production mechanism will increase the accuracy  ... 
doi:10.37917/ijeee.16.2.10 fatcat:crz5ieseo5g5nmcllbpm5oz22e

2 Machine learning approach to automatic recognition of emotions based on bioelectrical brain activity [chapter]

2020 Simulations in Medicine  
Automatic emotion recognition systems may help in diagnosis, monitoring, and rehabilitation.  ...  Nowadays machine learning methods, including deep learning, come with help along with the growing amount of available data.  ...  recognition of emotions Machine learning approach to automatic recognition of emotions Machine learning approach to automatic recognition of emotions Machine learning approach to automatic  ... 
doi:10.1515/9783110667219-002 fatcat:23zmbmlnkfe5hdadjx5sqpeb5i

Dual Exclusive Attentive Transfer for Unsupervised Deep Convolutional Domain Adaptation in Speech Emotion Recognition

Elias Nii Noi Ocquaye, Qirong Mao, Heping Song, Guopeng Xu, Yanfei Xue
2019 IEEE Access  
INDEX TERMS Attention transfer, correlation alignment, convolutional neural network, speech emotion recognition, unsupervised domain adaptation.  ...  Considering different corpora of speech emotions available both publicly and privately with numerous factors that make them different, the premise of having features of both training and testing samples  ...  INTRODUCTION Speech emotion recognition in affective computing has gained much recognition as a result of effectively predicting emotional states of speech automatically via different machine learning  ... 
doi:10.1109/access.2019.2924597 fatcat:eystcdogzba7ng2prr32kwxr2m

Latest trends in emotion recognition methods: case study on emotiw challenge

Huma Naz, Sachin Ahuja
2020 International Journal of Advanced Computer Research  
Emotion recognition is becoming increasingly very active field in research.  ...  Moreover, Emotion recognition models are used by more and more intelligent system to improve the multimodal interaction.  ...  Huma Naz and Sachin Ahuja  ... 
doi:10.19101/ijacr.2019.940117 fatcat:dkzmqvn4xrfslafxn2dbavjgni

Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages

Sneha Das, Nicklas Leander Lund, Nicole Nadine Lønfeldt, Anne Katrine Pagsberg, Line H. Clemmensen
2022 Proceedings of the Northern Lights Deep Learning Workshop  
Speech emotion recognition (SER) refers to the technique of inferring the emotional state of an individual from speech signals. SERs continue to garner interest due to their wide applicability.  ...  While the domain is mainly founded on signal processing, machine learning and deep learning methods, generalizing over languages continues to remain a challenge.  ...  Introduction Speech emotion recognition (SER) is the process of inferring the emotional state from speech signals.  ... 
doi:10.7557/18.6300 fatcat:na4emlzzhvdy5jfnc6mumbacwi

Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages [article]

Sneha Das, Nicklas Leander Lund, Nicole Nadine Lønfeldt, Anne Katrine Pagsberg, Line H. Clemmensen
2022 arXiv   pre-print
Speech emotion recognition~(SER) refers to the technique of inferring the emotional state of an individual from speech signals. SERs continue to garner interest due to their wide applicability.  ...  Although the domain is mainly founded on signal processing, machine learning, and deep learning, generalizing over languages continues to remain a challenge.  ...  Introduction Speech emotion recognition (SER) is the process of inferring the emotional state from speech signals.  ... 
arXiv:2203.14867v1 fatcat:26e3wdogizgu5arj37qa4evbme

Reviewing the connection between speech and obstructive sleep apnea

Fernando Espinoza-Cuadros, Rubén Fernández-Pozo, Doroteo T. Toledano, José D. Alcázar-Ramírez, Eduardo López-Gonzalo, Luis A. Hernández-Gómez
2016 BioMedical Engineering OnLine  
In this paper we critically review several approaches using speech analysis and machine learning techniques for OSA detection, and discuss the limitations that can arise when using machine learning techniques  ...  We hope this study could not only be a useful example of relevant issues when using machine learning for medical diagnosis, but it will also help in guiding further research on the connection between speech  ...  Acknowledgements Authors thank to Sonia Martínez Díaz for her effort in collecting the OSA database that is used in this study.  ... 
doi:10.1186/s12938-016-0138-5 pmid:26897500 pmcid:PMC4761156 fatcat:kfdxuxirm5bwvj47sqkjlt523q

Emotion Recognition in Speech using Cross-Modal Transfer in the Wild [article]

Samuel Albanie, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman
2018 arXiv   pre-print
a student, tabula rasa, to learn representations (embeddings) for speech emotion recognition without access to labelled audio data; and (iii) we show that the speech emotion embedding can be used for speech  ...  In this work, we consider the task of learning embeddings for speech classification without access to any form of labelled audio.  ...  The authors would like to thank the anonymous reviewers, Almut Sophia Koepke and Judith Albanie for useful suggestions.  ... 
arXiv:1808.05561v1 fatcat:v7qxqftj7fgljfxutt4sexf4iq

Emotion Recognition in Speech using Cross-Modal Transfer in the Wild

Samuel Albanie, Arsha Nagrani, Andrea Vedaldi, Andrew Zisserman
2018 2018 ACM Multimedia Conference on Multimedia Conference - MM '18  
The authors would like to thank the anonymous reviewers, Almut Sophia Koepke and Judith Albanie for useful suggestions.  ...  We gratefully acknowledge the support of EPSRC CDT AIMS grant EP/L015897/1, and the Programme Grant Seebibyte EP/M013774/1.  ...  Note that for any machine learning system that aims to perform emotion recognition using vision or speech, the ground truth emotional state of the speaker is typically unavailable.  ... 
doi:10.1145/3240508.3240578 dblp:conf/mm/AlbanieNVZ18 fatcat:6dp4ssc3lregxhxvvu7kb7nnji

Speech Emotion Recognition by Late Fusion for Bidirectional Reservoir Computing with Random Projection

Hemin Ibrahim, Chu Kiong Loo, Fady Alnajjar
2021 IEEE Access  
Many researchers are inspired by studying Speech Emotion Recognition (SER) because it is considered as a key effort in Human-Computer Interaction (HCI).  ...  Due to the time series and sparse nature of emotion in speech, we have adopted a multivariate time series feature representation of the input data.  ...  FEATURE EXTRACTION Speech features with discriminative information have a vital role in emotion recognition in speech.  ... 
doi:10.1109/access.2021.3107858 fatcat:qfnrr4y2u5drrpedajreyichdu
« Previous Showing results 1 — 15 out of 741 results