mlsanityData to 14 Oct 2026

Speech Emotion Recognition using Supervised Deep Recurrent System for Mental Health Monitoring

arXiv 2208.12812 ↗First posted 26 Aug 2022eess.AS cs.HC cs.LGcited by 15

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Abstract (arXiv)

Understanding human behavior and monitoring mental health are essential to maintaining the community and society's safety. As there has been an increase in mental health problems during the COVID-19 pandemic due to uncontrolled mental health, early detection of mental issues is crucial. Nowadays, the usage of Intelligent Virtual Personal Assistants (IVA) has increased worldwide. Individuals use their voices to control these devices to fulfill requests and acquire different services. This paper proposes a novel deep learning model based on the gated recurrent neural network and convolution neural network to understand human emotion from speech to improve their IVA services and monitor their mental health.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Builds on 6 of its 61 references that are in the map. First posted on arXiv 26 Aug 2022.

Builds on

6 of 61 references.

References · 6

  1. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,611
  2. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,367
  3. 20191D Convolutional Neural Networks and Applications: A Surveycited by 153
  4. 2019Dilated Convolution with Dilated GRU for Music Source Separationcited by 4
  5. 2013Improving Automatic Emotion Recognition from speech using Rhythm and Temporal featurecited by 3
  6. 2021Biologically inspired speech emotion recognitioncited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 3; 2025: 6; 2026: 3.

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  1. 2025Synthetic Data Generation by Supervised Neural Gas Network for Physiological Emotion Recognition Datacited by 4
  2. 2025EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognitioncited by 3
  3. 2023Active Learning Based Fine-Tuning Framework for Speech Emotion Recognitioncited by 2
  4. 2025Multi-Teacher Language-Aware Knowledge Distillation for Multilingual Speech Emotion Recognitioncited by 2
  5. 2023LiteLSTM Architecture Based on Weights Sharing for Recurrent Neural Networkscited by 1
  6. 2025CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognitioncited by 1
  7. 2023Human Behavior in the Time of COVID-19: Learning from Big Datacited by 0
  8. 2024TemporalAugmenter: An Ensemble Recurrent Based Deep Learning Approach for Signal Classificationcited by 0
  9. 2024Active Learning with Task Adaptation Pre-training for Speech Emotion Recognitioncited by 0
  10. 2024WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognitioncited by 0
  11. 2025Joint Learning using Mixture-of-Expert-Based Representation for Speech Enhancement and Robust Emotion Recognitioncited by 0
  12. 2025MI-Fuse: Label Fusion for Unsupervised Domain Adaptation with Closed-Source Large-Audio Language Modelcited by 0
3 more
  1. 2026Explainable Speech Emotion Recognition: Weighted Attribute Fairness to Model Demographic Contributions to Social Biascited by 0
  2. 2026Explainable Lightweight Compact Deep Models for Speech Emotion Recognitioncited by 0
  3. 2026Reading Emotions in the Token Space: Discriminative Adaptation of SpeechLLMs for Emotion Recognitioncited by 0