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An experimental study of speech emotion recognition based on deep convolutional neural networks
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Outgoing claims: the papers this work cites, builds on, or argues with.
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An Algorithm for Determining the Endpoints of Isolated Utterances
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Gradient-based learning applied to document recognition
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Features extraction and selection for emotional speech classification
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Multi-level Speech Emotion Recognition Based on HMM and ANN
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Automatic Speech Emotion Recognition using Support Vector Machine
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Automatic emotional speech classification
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GMM Supervector Based SVM with Spectral Features for Speech Emotion Recognition
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Emotion classification via utterance-level dynamics: A pattern-based approach to characterizing affective expressions
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Identifying salient sub-utterance emotion dynamics using flexible units and estimates of affective flow
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Bhattacharyya distance based emotional dissimilarity measure for emotion classification
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Hidden Markov model-based speech emotion recognition
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Mandarin Emotional Speech Recognition Based on SVM and NN
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Convolutional networks and applications in vision
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Feature Extraction and Selection for Emotion Recognition from EEG
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Representation Learning: A Review and New Perspectives
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Speech Emotion Recognition Using CNN
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ImageNet classification with deep convolutional neural networks
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Emotion recognition based on phoneme classes
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Speech emotion recognition using deep neural network and extreme learning machine
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Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks
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Speech Emotion Recognition using Support Vector Machine
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Emotions Classification from Speech with Deep Learning
inferred← citeshttps://doi.org/10.18178/ijmlc.2018.8.3.687openalex-snapshot
Speech Emotion Recognition Based on SVM and ANN
inferred← citeshttps://doi.org/10.18280/ts.380124openalex-snapshot
Classification of Pitch and Gender of Speakers for Forensic Speaker Recognition from Disguised Voices Using Novel Features Learned by Deep Convolutional Neural Networks
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2848786/v1openalex-snapshot
Automatic Speaker Identification System based MLP Network and Deep Learning in the Presence of Severe Interference
inferred← citeshttps://doi.org/10.21203/rs.3.rs-4018342/v1openalex-snapshot
Speech-based Sentiment Recognition System using PDCNN and LSTM Algorithms
inferred← citeshttps://doi.org/10.21437/interspeech.2018-1371openalex-snapshot
Impact of Aliasing on Deep CNN-Based End-to-End Acoustic Models
inferred← citeshttps://doi.org/10.21437/interspeech.2019-2710openalex-snapshot
Continuous Emotion Recognition in Speech — Do We Need Recurrence?
inferred← citeshttps://doi.org/10.21817/indjcse/2021/v12i1/211201187openalex-snapshot
EMOTION RECOGNITION IN STANDARD SPOKEN ASSAMESE LANGUAGE USING SUPPORT VECTOR MACHINE AND ENSEMBLE MODEL
inferred← citeshttps://doi.org/10.22214/ijraset.2022.41112openalex-snapshot
Speech Emotion Recognition System Using Recurrent Neural Network in Deep Learning
inferred← citeshttps://doi.org/10.22214/ijraset.2022.46884openalex-snapshot
Real Time Speech Recognition in 1-Dimensional Using Convolution Neural Network
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Automatic classification of emotions in speech: methods and data
inferred← citeshttps://doi.org/10.3233/apc210134openalex-snapshot
A Comparative Study of Detection and Classification of Emotions on Social Media Using SVM and Näıve Bayes Techniques
inferred← citeshttps://doi.org/10.32604/cmc.2021.015070openalex-snapshot
1D-CNN: Speech Emotion Recognition System Using a Stacked Network with Dilated CNN Features
inferred← citeshttps://doi.org/10.33093/jiwe.2022.1.2.4openalex-snapshot
Emotion Recognition by Facial Expression and Voice: Review and Analysis
inferred← citeshttps://doi.org/10.3389/fpsyg.2024.1357975openalex-snapshot
Emotional responses of Korean and Chinese women to Hangul phonemes to the gender of an artificial intelligence voice
inferred← citeshttps://doi.org/10.3389/frobt.2020.532279openalex-snapshot
Emotion Recognition for Human-Robot Interaction: Recent Advances and Future Perspectives
inferred← citeshttps://doi.org/10.3390/app10010205openalex-snapshot
An Ensemble Model for Multi-Level Speech Emotion Recognition
inferred← citeshttps://doi.org/10.3390/app10093286openalex-snapshot
Bioacoustic Classification of Antillean Manatee Vocalization Spectrograms Using Deep Convolutional Neural Networks
inferred← citeshttps://doi.org/10.3390/app16083800openalex-snapshot
DC-MEPV: Dual-Channel Assisted Music Emotion Perception and Visualization in Acousto-Optic Synergistic Intelligent Cockpits
inferred← citeshttps://doi.org/10.3390/computation5020026openalex-snapshot
Deep Visual Attributes vs. Hand-Crafted Audio Features on Multidomain Speech Emotion Recognition
inferred← citeshttps://doi.org/10.3390/electronics11223831openalex-snapshot
Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
inferred← citeshttps://doi.org/10.3390/info16030238openalex-snapshot
Speech Emotion Recognition and Serious Games: An Entertaining Approach for Crowdsourcing Annotated Samples
inferred← citeshttps://doi.org/10.3390/jimaging11080273openalex-snapshot
Bangla Speech Emotion Recognition Using Deep Learning-Based Ensemble Learning and Feature Fusion
inferred← citeshttps://doi.org/10.3390/math8122133openalex-snapshot
CLSTM: Deep Feature-Based Speech Emotion Recognition Using the Hierarchical ConvLSTM Network
inferred← citeshttps://doi.org/10.3390/s20185212openalex-snapshot
Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features
inferred← citeshttps://doi.org/10.3390/s20226688openalex-snapshot
Fusion-ConvBERT: Parallel Convolution and BERT Fusion for Speech Emotion Recognition
inferred← citeshttps://doi.org/10.3390/s21051579openalex-snapshot
Multi-Path and Group-Loss-Based Network for Speech Emotion Recognition in Multi-Domain Datasets
inferred← citeshttps://doi.org/10.3390/s22062378openalex-snapshot
Two-Way Feature Extraction for Speech Emotion Recognition Using Deep Learning
inferred← citeshttps://doi.org/10.34133/icomputing.0073openalex-snapshot
Temporal Shift Module with Pretrained Representations for Speech Emotion Recognition
inferred← citeshttps://doi.org/10.35784/acs_8130openalex-snapshot
K4F-Net: Lightweight multi-view speech emotion recognition with Kronecker convolution and cross-language robustness
inferred← citeshttps://doi.org/10.35940/ijeat.a1068.1291s52019openalex-snapshot
Machine Learning Based Emotion Recognition using Speech Signal
inferred← citeshttps://doi.org/10.35940/ijeat.e1027.069520openalex-snapshot
A Hybrid Technique using CNN LSTM for Speech Emotion Recognition
inferred← citeshttps://doi.org/10.3844/jcssp.2018.1577.1587openalex-snapshot
Deep Learning Models for Speech Emotion Recognition
inferred← citeshttps://doi.org/10.3990/1.9789036545839openalex-snapshot
Automatic recognition of engagement and emotion in a group of children
inferred← citeshttps://doi.org/10.4018/979-8-3373-7082-8.ch011openalex-snapshot
AI Music Genre Classification via Inception-RNN With Multi-Scale Temporal Features
inferred← citeshttps://doi.org/10.4236/jbise.2016.910b005openalex-snapshot
Feature Optimization of Speech Emotion Recognition
inferred← citeshttps://doi.org/10.48550/arxiv.1707.09917openalex-snapshot
A breakthrough in Speech emotion recognition using Deep Retinal Convolution Neural Networks
inferred← citeshttps://doi.org/10.48550/arxiv.1906.05681openalex-snapshot
Deep Learning based Emotion Recognition System Using Speech Features and Transcriptions
inferred← citeshttps://doi.org/10.48550/arxiv.1906.05682openalex-snapshot
Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition
inferred← citeshttps://doi.org/10.48550/arxiv.2001.00378openalex-snapshot
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends
inferred← citeshttps://doi.org/10.5204/thesis.eprints.180753openalex-snapshot
Multimodal emotion recognition using deep learning techniques
inferred← citeshttps://doi.org/10.5755/j01.itc.52.4.34079openalex-snapshot
MPCM: Multi-modal User Portrait Classification Model Based on Collaborative Learning
inferred← citeshttps://doi.org/10.5815/ijmsc.2021.01.04openalex-snapshot
A System to Predict Emotion from Bengali Speech
inferred← citeshttps://doi.org/10.7282/t3-s7ze-0304openalex-snapshot
Speech-based affective computing using attention with multimodal fusion
inferred← citeshttps://doi.org/10.7717/peerj-cs.246openalex-snapshot
Linking emotions to behaviors through deep transfer learning
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