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Speech Emotion Recognition Based on Deep Residual Shrinkage Network

https://doi.org/10.3390/electronics12112512

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-68780-9_25openalex-snapshot

Multimodal Emotion Recognition Based on Speech and Physiological Signals Using Deep Neural Networks

inferredcites →https://doi.org/10.1007/978-981-19-1677-9_17openalex-snapshot

PCA-Based Random Forest Classifier for Speech Emotion Recognition Using FFTF Features, Jitter, and Shimmer

inferredcites →https://doi.org/10.1007/s00034-020-01429-3openalex-snapshot

Attention and Feature Selection for Automatic Speech Emotion Recognition Using Utterance and Syllable-Level Prosodic Features

inferredcites →https://doi.org/10.1007/s00034-020-01486-8openalex-snapshot

DNN-HMM-Based Speaker-Adaptive Emotion Recognition Using MFCC and Epoch-Based Features

inferredcites →https://doi.org/10.1007/s11042-022-13725-yopenalex-snapshot

Speech emotion recognition by using complex MFCC and deep sequential model

inferredcites →https://doi.org/10.1007/s12652-016-0406-zopenalex-snapshot

CHEAVD: a Chinese natural emotional audio–visual database

inferredcites →https://doi.org/10.1016/j.apacoust.2020.107360openalex-snapshot

Speech emotion recognition using hybrid spectral-prosodic features of speech signal/glottal waveform, metaheuristic-based dimensionality reduction, and Gaussian elliptical basis function network classifier

inferredcites →https://doi.org/10.1016/j.bspc.2018.08.035openalex-snapshot

Speech emotion recognition using deep 1D & 2D CNN LSTM networks

inferredcites →https://doi.org/10.1016/j.bspc.2020.101894openalex-snapshot

Speech emotion recognition with deep convolutional neural networks

inferredcites →https://doi.org/10.1016/j.knosys.2019.104886openalex-snapshot

Bagged support vector machines for emotion recognition from speech

inferredcites →https://doi.org/10.1016/j.neucom.2017.07.050openalex-snapshot

Speech emotion recognition based on feature selection and extreme learning machine decision tree

inferredcites →https://doi.org/10.1016/j.specom.2019.10.004openalex-snapshot

Speech emotion recognition based on DNN-decision tree SVM model

inferredcites →https://doi.org/10.1016/j.specom.2019.12.001openalex-snapshot

Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers

inferredcites →https://doi.org/10.1088/1742-6596/1896/1/012004openalex-snapshot

Evaluation of error- and correlation-based loss functions for multitask learning dimensional speech emotion recognition

inferredcites →https://doi.org/10.1109/access.2019.2901352openalex-snapshot

Emotion Recognition Using Hybrid Gaussian Mixture Model and Deep Neural Network

inferredcites →https://doi.org/10.1109/access.2019.2928625openalex-snapshot

Exploring Deep Spectrum Representations via Attention-Based Recurrent and Convolutional Neural Networks for Speech Emotion Recognition

inferredcites →https://doi.org/10.1109/access.2020.2990405openalex-snapshot

Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM

inferredcites →https://doi.org/10.1109/access.2020.3017462openalex-snapshot

End-to-End Speech Emotion Recognition With Gender Information

inferredcites →https://doi.org/10.1109/access.2021.3068045openalex-snapshot

A Comprehensive Review of Speech Emotion Recognition Systems

inferredcites →https://doi.org/10.1109/icassp43922.2022.9747095openalex-snapshot

Speech Emotion Recognition with Co-Attention Based Multi-Level Acoustic Information

inferredcites →https://doi.org/10.1109/ist55454.2022.9827732openalex-snapshot

Transformer-CNN Automatic Hyperparameter Tuning for Speech Emotion Recognition

inferredcites →https://doi.org/10.1109/tmm.2017.2766843openalex-snapshot

Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching

inferredcites →https://doi.org/10.18178/ijmlc.2018.8.3.687openalex-snapshot

Speech Emotion Recognition Based on SVM and ANN

inferredcites →https://doi.org/10.18653/v1/p19-1050openalex-snapshot

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

inferredcites →https://doi.org/10.21437/interspeech.2018-2298openalex-snapshot

LSTM Based Cross-corpus and Cross-task Acoustic Emotion Recognition

inferredcites →https://doi.org/10.21437/interspeech.2020-1391openalex-snapshot

Learning Utterance-Level Representations with Label Smoothing for Speech Emotion Recognition

inferredcites →https://doi.org/10.21437/interspeech.2020-2524openalex-snapshot

Speech Representation Learning for Emotion Recognition Using End-to-End ASR with Factorized Adaptation

inferredcites →https://doi.org/10.21437/interspeech.2021-2004openalex-snapshot

Learning Mutual Correlation in Multimodal Transformer for Speech Emotion Recognition

inferredcites →https://doi.org/10.3390/a13030070openalex-snapshot

Ensemble Learning of Hybrid Acoustic Features for Speech Emotion Recognition

inferredcites →https://doi.org/10.3390/electronics12040839openalex-snapshot

Speech Emotion Recognition Based on Multiple Acoustic Features and Deep Convolutional Neural Network

inferredcites →https://doi.org/10.3390/electronics9050713openalex-snapshot

Attention-LSTM-Attention Model for Speech Emotion Recognition and Analysis of IEMOCAP Database

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Enhancing Speech and Emotion Recognition Via Hierarchical Capsule Networks with Gated Recurrent Units and Attention Mechanism: A Comprehensive Study

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CNN-BiLSTM Hybrid Neural Network Deep Learning Model for Flight Pilot Stress Detection

inferred← citeshttps://doi.org/10.1007/s10772-023-10080-7openalex-snapshot

CCTG-NET: Contextualized Convolutional Transformer-GRU Network for speech emotion recognition

inferred← citeshttps://doi.org/10.1016/j.artmed.2025.103279openalex-snapshot

TSFNet: A Temporal–Spectral Fusion Network for advanced speech emotion recognition in medical applications

inferred← citeshttps://doi.org/10.1016/j.asoc.2026.116602openalex-snapshot

Multimodal speech emotion recognition based on dual cross-modal attention mechanism

inferred← citeshttps://doi.org/10.1016/j.bspc.2025.107860openalex-snapshot

A comprehensive approach to enhance emotion recognition through advanced feature extraction and Attention

inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122946openalex-snapshot

MSER: Multimodal speech emotion recognition using cross-attention with deep fusion

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MER-CAPF: Audio-text emotion recognition through cross-attention mechanism and multi-granularity pooling strategy

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Automated gall bladder cancer detection using artificial gorilla troops optimizer with transfer learning on ultrasound images

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An efficient deep learning framework for mixed-type wafer map defect pattern recognition

inferred← citeshttps://doi.org/10.1109/icspcc59353.2023.10400357openalex-snapshot

Speech Emotion Recognition Based on Feature Fusion and Residual Graph Convolutional Network

inferred← citeshttps://doi.org/10.1109/icssas66150.2025.11081375openalex-snapshot

Enhancing Speech Emotion Recognition Accuracy using BiGRU Network

inferred← citeshttps://doi.org/10.1109/ijcnn60899.2024.10650087openalex-snapshot

Improving Speech Emotion Recognition through Hierarchical Classification and Text Integration for Enhanced Emotional Analysis and Contextual Understanding

inferred← citeshttps://doi.org/10.1109/tcss.2025.3625592openalex-snapshot

Neonatal Pain Speech Emotion Recognition Based on Multiscale Multilevel MAE Network

inferred← citeshttps://doi.org/10.1145/3696409.3700257openalex-snapshot

DCEPNet: Dual-Channel Emotional Perception Network for Speech Emotion Recognition

inferred← citeshttps://doi.org/10.1186/s12302-024-00841-9openalex-snapshot

Gaussian mutation–orca predation algorithm–deep residual shrinkage network (DRSN)–temporal convolutional network (TCN)–random forest model: an advanced machine learning model for predicting monthly rainfall and filtering irrelevant data

inferred← citeshttps://doi.org/10.1186/s40537-025-01090-0openalex-snapshot

Developing a negative speech emotion recognition model for safety systems using deep learning

inferred← citeshttps://doi.org/10.1587/transinf.2024edp7117openalex-snapshot

An Anchor-Free Siamese Tracker with Multi-Attention and Corner Detection Mechanism

inferred← citeshttps://doi.org/10.21203/rs.3.rs-3942784/v1openalex-snapshot

A Survey on Multi-modal Emotion Detection Techniques

inferred← citeshttps://doi.org/10.3390/app131910834openalex-snapshot

Non-Intrusive Air Traffic Control Speech Quality Assessment with ResNet-BiLSTM

inferred← citeshttps://doi.org/10.3390/electronics12122704openalex-snapshot

Text Emotion Recognition Based on XLNet-BiGRU-Att

inferred← citeshttps://doi.org/10.3390/electronics12234779openalex-snapshot

Genetic Algorithm for High-Dimensional Emotion Recognition from Speech Signals

inferred← citeshttps://doi.org/10.3390/signals6020022openalex-snapshot

Speech Emotion Recognition: Comparative Analysis of CNN-LSTM and Attention-Enhanced CNN-LSTM Models

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