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EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion Recognition

https://doi.org/10.1109/taffc.2021.3135152

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

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Note on the Sampling Error of the Difference Between Correlated Proportions or Percentages

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Efficient and effective strategies for cross-corpus acoustic emotion recognition

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Survey on speech emotion recognition: Features, classification schemes, and databases

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A review of depression and suicide risk assessment using speech analysis

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Verbal and Nonverbal Communication of Deception

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Emotional Intelligence in Everyday Life

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Emotional intelligence meets traditional standards for an intelligence

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Speech emotion recognition using hidden Markov models

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Analysis and compensation of speech under stress and noise for environmental robustness in speech recognition

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Emotional intelligence as a standard intelligence.

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Acoustic profiles in vocal emotion expression.

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Emotional intelligence as a standard intelligence.

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Introducing the Geneva Multimodal expression corpus for experimental research on emotion perception.

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A circumplex model of affect.

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Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants

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Nonlinear feature based classification of speech under stress

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Sentiment analysis using image-based deep spectrum features

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Unsupervised learning in cross-corpus acoustic emotion recognition

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ImageNet: A large-scale hierarchical image database

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Rethinking the Inception Architecture for Computer Vision

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Deep Residual Learning for Image Recognition

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Adversarial Discriminative Domain Adaptation

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Usage of emotion recognition in military health care

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Audiovisual Behavior Modeling by Combined Feature Spaces

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Supervised domain adaptation for emotion recognition from speech

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CNN architectures for large-scale audio classification

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Audio Set: An ontology and human-labeled dataset for audio events

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Automatic speech emotion recognition using recurrent neural networks with local attention

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Multimodal Bag-of-Words for Cross Domains Sentiment Analysis

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End-to-End Speech Emotion Recognition Using Deep Neural Networks

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The Role of Task and Acoustic Similarity in Audio Transfer Learning: Insights from the Speech Emotion Recognition Case

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Online Multi-object Tracking Using CNN-Based Single Object Tracker with Spatial-Temporal Attention Mechanism

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The eNTERFACE’05 Audio-Visual Emotion Database

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From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification

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Real time speech emotion recognition using RGB image classification and transfer learning

inferredcites →https://doi.org/10.1109/ijcnn.2018.8489416openalex-snapshot

Bag-of-Deep-Features: Noise-Robust Deep Feature Representations for Audio Analysis

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Activity and emotion recognition to support early diagnosis of psychiatric diseases

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Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies

inferredcites →https://doi.org/10.1109/taffc.2015.2457417openalex-snapshot

The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing

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AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild

inferredcites →https://doi.org/10.1109/taffc.2018.2858255openalex-snapshot

Feature Pooling of Modulation Spectrum Features for Improved Speech Emotion Recognition in the Wild

inferredcites →https://doi.org/10.1109/tasl.2013.2255278openalex-snapshot

On Acoustic Emotion Recognition: Compensating for Covariate Shift

inferredcites →https://doi.org/10.1109/taslp.2020.3030497openalex-snapshot

PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition

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Detection of Clinical Depression in Adolescents’ Speech During Family Interactions

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“Are You Playing a Shooter Again?!” Deep Representation Learning for Audio-Based Video Game Genre Recognition

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Dataset Shift in Machine Learning

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Diagnosis of depression by behavioural signals

inferredcites →https://doi.org/10.1145/2663204.2666275openalex-snapshot

Emotion Recognition In The Wild Challenge 2014

inferredcites →https://doi.org/10.1145/3065386openalex-snapshot

ImageNet classification with deep convolutional neural networks

inferredcites →https://doi.org/10.1145/3123266.3123371openalex-snapshot

An Image-based Deep Spectrum Feature Representation for the Recognition of Emotional Speech

inferredcites →https://doi.org/10.1145/3129340openalex-snapshot

Speech emotion recognition

inferredcites →https://doi.org/10.1145/3267935.3267948openalex-snapshot

Deep Spectrum Feature Representations for Speech Emotion Recognition

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Group-level Speech Emotion Recognition Utilising Deep Spectrum Features

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Deep Dominance - How to Properly Compare Deep Neural Models

inferredcites →https://doi.org/10.21437/eurospeech.1997-482openalex-snapshot

Design, recording and verification of a danish emotional speech database

inferredcites →https://doi.org/10.21437/eurospeech.1997-494openalex-snapshot

Getting started with SUSAS: a speech under simulated and actual stress database

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A database of German emotional speech

inferredcites →https://doi.org/10.21437/interspeech.2011-468openalex-snapshot

Using multiple databases for training in emotion recognition: to unite or to vote?

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An investigation of depressed speech detection: features and normalization

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Is Deception Emotional? An Emotion-Driven Predictive Approach

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An Investigation of Emotional Speech in Depression Classification

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Snore Sound Classification Using Image-Based Deep Spectrum Features

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Towards Speech Emotion Recognition “in the Wild” Using Aggregated Corpora and Deep Multi-Task Learning

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Attentive Convolutional Neural Network Based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech

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VoxCeleb: A Large-Scale Speaker Identification Dataset

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Attention-based Sequence Classification for Affect Detection

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The INTERSPEECH 2018 Computational Paralinguistics Challenge: Atypical & Self-Assessed Affect, Crying & Heart Beats

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Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model

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Meta-Learning for Speech Emotion Recognition Considering Ambiguity of Emotion Labels

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An Efficient Temporal Modeling Approach for Speech Emotion Recognition by Mapping Varied Duration Sentences into Fixed Number of Chunks

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Deep Architecture Enhancing Robustness to Noise, Adversarial Attacks, and Cross-Corpus Setting for Speech Emotion Recognition

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Emotional Intelligence

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Attention Based Fully Convolutional Network for Speech Emotion Recognition

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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Unsupervised Domain Adaptation by Backpropagation

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Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

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Adversarial Discriminative Domain Adaptation

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Learning multiple visual domains with residual adapters

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Attentional Pooling for Action Recognition

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Conversational AI: The Science Behind the Alexa Prize

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Wide Residual Networks

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The SmartKom Multimodal Corpus at BAS

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Common Sense, the Turing Test, and the Quest for Real AI

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Emotion and Personality in a Conversational Agent

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Dataset Shift in Machine Learning

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

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Learning Common Semantics via Optimal Transport for Contrastive Multi-View Clustering

inferred← citeshttps://doi.org/10.1109/tpami.2023.3325770openalex-snapshot

COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition

inferred← citeshttps://doi.org/10.1109/ubmk63289.2024.10773591openalex-snapshot

Semantic Knowledge Base for the Emotional Coloring Analysis of Kazakh Texts

inferred← citeshttps://doi.org/10.1145/3503161.3551792openalex-snapshot

MuSe 2022 Challenge

inferred← citeshttps://doi.org/10.1145/3551876.3554800openalex-snapshot

A Personalised Approach to Audiovisual Humour Recognition and its Individual-level Fairness

inferred← citeshttps://doi.org/10.1145/3551876.3554817openalex-snapshot

The MuSe 2022 Multimodal Sentiment Analysis Challenge

inferred← citeshttps://doi.org/10.1145/3606039.3613114openalex-snapshot

The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked Emotions, Cross-Cultural Humour, and Personalisation

inferred← citeshttps://doi.org/10.1145/3662739.3672322openalex-snapshot

Application of Transfer Learning-Based English Speech Emotion Recognition in Real-World Scenarios

inferred← citeshttps://doi.org/10.1145/3689062.3689088openalex-snapshot

The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition

inferred← citeshttps://doi.org/10.2139/ssrn.4455697openalex-snapshot

Advancements in Speech Based Emotion Identification Models Using Deep Learning: A Comprehensive Overview

inferred← citeshttps://doi.org/10.3389/frai.2022.856232openalex-snapshot

DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing From Decentralized Data

inferred← citeshttps://doi.org/10.3390/a17030090openalex-snapshot

Optimizing Speech Emotion Recognition with Deep Learning and Grey Wolf Optimization: A Multi-Dataset Approach

inferred← citeshttps://doi.org/10.3390/app122412805openalex-snapshot

MSFL: Explainable Multitask-Based Shared Feature Learning for Multilingual Speech Emotion Recognition

inferred← citeshttps://doi.org/10.3390/app13116409openalex-snapshot

Fast and Accurate Facial Expression Image Classification and Regression Method Based on Knowledge Distillation

inferred← citeshttps://doi.org/10.3390/app15105731openalex-snapshot

Review of Automatic Estimation of Emotions in Speech

inferred← citeshttps://doi.org/10.3390/app16189333openalex-snapshot

Towards Unified Affective AI: A Cross-Modal Survey of Emotion Recognition, Generation, and Control

inferred← citeshttps://doi.org/10.3390/data10100164openalex-snapshot

Review and Comparative Analysis of Databases for Speech Emotion Recognition

inferred← citeshttps://doi.org/10.3390/math11163519openalex-snapshot

Multi-Corpus Learning for Audio–Visual Emotions and Sentiment Recognition

inferred← citeshttps://doi.org/10.3390/s25041270openalex-snapshot

Interpretable Probabilistic Identification of Depression in Speech

inferred← citeshttps://doi.org/10.36227/techrxiv.171441660.05393293/v1openalex-snapshot

A Multi-Scale Complex Feature Refinement and Dynamic Convolution Attention-Aware Network for Depression and ADHD Assessment Using Speech

inferred← citeshttps://doi.org/10.36227/techrxiv.21309600openalex-snapshot

A Residual Multi-Scale Convolutional Transformer Network with Chunk-level Log-Mel Spectrograms for Speech Emotion Recognition

inferred← citeshttps://doi.org/10.36227/techrxiv.21309600.v1openalex-snapshot

A Residual Multi-Scale Convolutional Transformer Network with Chunk-level Log-Mel Spectrograms for Speech Emotion Recognition

inferred← citeshttps://doi.org/10.3788/irla20250129openalex-snapshot

基于多模态表情编码与时序建模的三维人脸重建

inferred← citeshttps://doi.org/10.4018/979-8-3373-6516-9.ch006openalex-snapshot

Sentiment and Emotion Analysis in Video Interviews Using Deep Learning Techniques

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