{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/emotion-recognition/papers/9","list_of":"/task/emotion-recognition","task":"Emotion Recognition","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":9,"pages_in_order":21,"rows_per_page":100,"rows":[801,900],"of":2041,"counts":{"archive_papers_tagged":2041,"with_a_code_link":614,"where_syntology_ran_a_sample":69,"not_listed_spam_title":0,"listed":2041,"listed_where_code_ran":69,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":60,"every_run_a_failure_of_syntologys_instrument":9,"listed_with_a_run_with_no_instrument_failure":60,"listed_every_run_a_failure_of_syntologys_instrument":9,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/emotion-recognition","prev":"/task/emotion-recognition/papers/8","next":"/task/emotion-recognition/papers/10","papers":[{"url":null,"slug":"aer-llm-ambiguity-aware-emotion-recognition","title":"AER-LLM: Ambiguity-aware Emotion Recognition Leveraging Large Language Models","date":"2024-09-26","arxiv_id":"2409.18339","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-acoustic-similarity-in-emotional","title":"Exploring Acoustic Similarity in Emotional Speech and Music via Self-Supervised Representations","date":"2024-09-26","arxiv_id":"2409.17899","repositories_listed":0,"syntology":null},{"url":null,"slug":"evofa-evolvable-fast-adaptation-for-eeg","title":"EvoFA: Evolvable Fast Adaptation for EEG Emotion Recognition","date":"2024-09-24","arxiv_id":"2409.15733","repositories_listed":0,"syntology":null},{"url":null,"slug":"ca-mhfa-a-context-aware-multi-head-factorized","title":"CA-MHFA: A Context-Aware Multi-Head Factorized Attentive Pooling for SSL-Based Speaker Verification","date":"2024-09-23","arxiv_id":"2409.15234","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-emotion-recognition-accuracy-with","title":"Improving Emotion Recognition Accuracy with Personalized Clustering","date":"2024-09-23","arxiv_id":"2410.03696","repositories_listed":0,"syntology":null},{"url":null,"slug":"avengers-assemble-amalgamation-of-non","title":"Avengers Assemble: Amalgamation of Non-Semantic Features for Depression Detection","date":"2024-09-22","arxiv_id":"2409.14312","repositories_listed":0,"syntology":null},{"url":null,"slug":"strong-alone-stronger-together-synergizing","title":"Strong Alone, Stronger Together: Synergizing Modality-Binding Foundation Models with Optimal Transport for Non-Verbal Emotion Recognition","date":"2024-09-21","arxiv_id":"2409.14221","repositories_listed":0,"syntology":null},{"url":null,"slug":"emotionqueen-a-benchmark-for-evaluating","title":"EmotionQueen: A Benchmark for Evaluating Empathy of Large Language Models","date":"2024-09-20","arxiv_id":"2409.13359","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-speech-emotion-recognition-in","title":"Personalized Speech Emotion Recognition in Human-Robot Interaction using Vision Transformers","date":"2024-09-16","arxiv_id":"2409.10687","repositories_listed":0,"syntology":null},{"url":null,"slug":"reflectdiffu-reflect-between-emotion-intent","title":"ReflectDiffu:Reflect between Emotion-intent Contagion and Mimicry for Empathetic Response Generation via a RL-Diffusion Framework","date":"2024-09-16","arxiv_id":"2409.10289","repositories_listed":0,"syntology":null},{"url":null,"slug":"stimulus-modality-matters-impact-of","title":"Stimulus Modality Matters: Impact of Perceptual Evaluations from Different Modalities on Speech Emotion Recognition System Performance","date":"2024-09-16","arxiv_id":"2409.10762","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-based-generative-error","title":"Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition","date":"2024-09-15","arxiv_id":"2409.09785","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-microphone-and-multi-modal-emotion","title":"Multi-Microphone and Multi-Modal Emotion Recognition in Reverberant Environment","date":"2024-09-14","arxiv_id":"2409.09545","repositories_listed":0,"syntology":null},{"url":null,"slug":"turbo-your-multi-modal-classification-with","title":"Turbo your multi-modal classification with contrastive learning","date":"2024-09-14","arxiv_id":"2409.09282","repositories_listed":0,"syntology":null},{"url":null,"slug":"early-joint-learning-of-emotion-information","title":"Early Joint Learning of Emotion Information Makes MultiModal Model Understand You Better","date":"2024-09-12","arxiv_id":"2409.18971","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-emotion-recognition-with-vision","title":"Multimodal Emotion Recognition with Vision-language Prompting and Modality Dropout","date":"2024-09-11","arxiv_id":"2409.07078","repositories_listed":0,"syntology":null},{"url":null,"slug":"apex-attention-on-personality-based-emotion","title":"APEX: Attention on Personality based Emotion ReXgnition Framework","date":"2024-09-10","arxiv_id":"2409.06118","repositories_listed":0,"syntology":null},{"url":null,"slug":"complex-emotion-recognition-system-using","title":"Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review","date":"2024-09-09","arxiv_id":"2409.07493","repositories_listed":0,"syntology":null},{"url":null,"slug":"consensus-based-distributed-quantum-kernel","title":"Consensus-based Distributed Quantum Kernel Learning for Speech Recognition","date":"2024-09-09","arxiv_id":"2409.05770","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-guided-fusion-techniques-for-multimodal","title":"Audio-Guided Fusion Techniques for Multimodal Emotion Analysis","date":"2024-09-08","arxiv_id":"2409.05007","repositories_listed":0,"syntology":null},{"url":null,"slug":"better-spanish-emotion-recognition-in-the","title":"Better Spanish Emotion Recognition In-the-wild: Bringing Attention to Deep Spectrum Voice Analysis","date":"2024-09-08","arxiv_id":"2409.05148","repositories_listed":0,"syntology":null},{"url":null,"slug":"searching-for-effective-preprocessing-method","title":"Searching for Effective Preprocessing Method and CNN-based Architecture with Efficient Channel Attention on Speech Emotion Recognition","date":"2024-09-06","arxiv_id":"2409.04007","repositories_listed":0,"syntology":null},{"url":null,"slug":"progressive-residual-extraction-based-pre","title":"Progressive Residual Extraction based Pre-training for Speech Representation Learning","date":"2024-08-31","arxiv_id":"2409.00387","repositories_listed":0,"syntology":null},{"url":null,"slug":"nus-emo-at-semeval-2024-task-3-instruction","title":"NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations","date":"2024-08-22","arxiv_id":"2501.17261","repositories_listed":0,"syntology":null},{"url":null,"slug":"recording-brain-activity-while-listening-to","title":"Recording Brain Activity While Listening to Music Using Wearable EEG Devices Combined with Bidirectional Long Short-Term Memory Networks","date":"2024-08-22","arxiv_id":"2408.12124","repositories_listed":0,"syntology":null},{"url":null,"slug":"sentiment-and-emotion-aware-multi-criteria","title":"Sentiment and Emotion-aware Multi-criteria Fuzzy Group Decision Making System","date":"2024-08-21","arxiv_id":"2408.11976","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-emotion-open-vocabulary-recognition","title":"Video Emotion Open-vocabulary Recognition Based on Multimodal Large Language Model","date":"2024-08-21","arxiv_id":"2408.11286","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoding-human-emotions-analyzing-multi","title":"Decoding Human Emotions: Analyzing Multi-Channel EEG Data using LSTM Networks","date":"2024-08-19","arxiv_id":"2408.10328","repositories_listed":0,"syntology":null},{"url":null,"slug":"eeg-scmm-soft-contrastive-masked-modeling-for","title":"EEG-SCMM: Soft Contrastive Masked Modeling for Cross-Corpus EEG-Based Emotion Recognition","date":"2024-08-17","arxiv_id":"2408.09186","repositories_listed":0,"syntology":null},{"url":null,"slug":"electroencephalogram-emotion-recognition-via","title":"Electroencephalogram Emotion Recognition via AUC Maximization","date":"2024-08-16","arxiv_id":"2408.08979","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-a-dialogue-system-using-a-large","title":"Toward a Dialogue System Using a Large Language Model to Recognize User Emotions with a Camera","date":"2024-08-15","arxiv_id":"2408.07982","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-deep-learning-for-group-level","title":"A Survey of Deep Learning for Group-level Emotion Recognition","date":"2024-08-13","arxiv_id":"2408.15276","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-on-eeg-based-emotion","title":"A Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective","date":"2024-08-12","arxiv_id":"2408.06027","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-enhancement-for-computer-audition-an","title":"Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance","date":"2024-08-12","arxiv_id":"2408.06264","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-generative-approach-for-emotion","title":"Towards a Generative Approach for Emotion Detection and Reasoning","date":"2024-08-09","arxiv_id":"2408.04906","repositories_listed":0,"syntology":null},{"url":null,"slug":"lldif-diffusion-models-for-low-light-emotion","title":"LLDif: Diffusion Models for Low-light Emotion Recognition","date":"2024-08-08","arxiv_id":"2408.04235","repositories_listed":0,"syntology":null},{"url":null,"slug":"recognizing-emotion-regulation-strategies","title":"Recognizing Emotion Regulation Strategies from Human Behavior with Large Language Models","date":"2024-08-08","arxiv_id":"2408.04420","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03150","title":"Conditioning LLMs with Emotion in Neural Machine Translation","date":"2024-08-06","arxiv_id":"2408.03150","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02421","title":"FE-Adapter: Adapting Image-based Emotion Classifiers to Videos","date":"2024-08-05","arxiv_id":"2408.02421","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-source-eeg-emotion-recognition-via","title":"Multi-Source EEG Emotion Recognition via Dynamic Contrastive Domain Adaptation","date":"2024-08-04","arxiv_id":"2408.10235","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01728","title":"Survey on Emotion Recognition through Posture Detection and the possibility of its application in Virtual Reality","date":"2024-08-03","arxiv_id":"2408.01728","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01838","title":"Tracking Emotional Dynamics in Chat Conversations: A Hybrid Approach using DistilBERT and Emoji Sentiment Analysis","date":"2024-08-03","arxiv_id":"2408.01838","repositories_listed":0,"syntology":null},{"url":null,"slug":"dua-dual-attentive-transformer-in-long-term","title":"DuA: Dual Attentive Transformer in Long-Term Continuous EEG Emotion Analysis","date":"2024-07-30","arxiv_id":"2407.20519","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21066","title":"ELP-Adapters: Parameter Efficient Adapter Tuning for Various Speech Processing Tasks","date":"2024-07-28","arxiv_id":"2407.21066","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-emotion-recognition-with-wearable","title":"Optimizing Emotion Recognition with Wearable Sensor Data: Unveiling Patterns in Body Movements and Heart Rate through Random Forest Hyperparameter Tuning","date":"2024-07-28","arxiv_id":"2408.03958","repositories_listed":0,"syntology":null},{"url":null,"slug":"describe-where-you-are-improving-noise","title":"Describe Where You Are: Improving Noise-Robustness for Speech Emotion Recognition with Text Description of the Environment","date":"2024-07-25","arxiv_id":"2407.17716","repositories_listed":0,"syntology":null},{"url":null,"slug":"erit-lightweight-multimodal-dataset-for","title":"ERIT Lightweight Multimodal Dataset for Elderly Emotion Recognition and Multimodal Fusion Evaluation","date":"2024-07-25","arxiv_id":"2407.17772","repositories_listed":0,"syntology":null},{"url":null,"slug":"masked-graph-learning-with-recurrent","title":"Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversation","date":"2024-07-23","arxiv_id":"2407.16714","repositories_listed":0,"syntology":null},{"url":null,"slug":"microemo-time-sensitive-multimodal-emotion","title":"MicroEmo: Time-Sensitive Multimodal Emotion Recognition with Micro-Expression Dynamics in Video Dialogues","date":"2024-07-23","arxiv_id":"2407.16552","repositories_listed":0,"syntology":null},{"url":null,"slug":"emo-codec-a-depth-look-at-emotion","title":"EMO-Codec: An In-Depth Look at Emotion Preservation capacity of Legacy and Neural Codec Models With Subjective and Objective Evaluations","date":"2024-07-22","arxiv_id":"2407.15458","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-tale-of-single-channel-electroencephalogram","title":"A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future Directions","date":"2024-07-20","arxiv_id":"2407.14850","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-explainable-fast-deep-neural-network-for","title":"An Explainable Fast Deep Neural Network for Emotion Recognition","date":"2024-07-20","arxiv_id":"2407.14865","repositories_listed":0,"syntology":null},{"url":null,"slug":"eegmamba-bidirectional-state-space-models","title":"EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification","date":"2024-07-20","arxiv_id":"2407.20254","repositories_listed":0,"syntology":null},{"url":null,"slug":"mapping-the-technological-future-a-topic","title":"Mapping the Technological Future: A Topic, Sentiment, and Emotion Analysis in Social Media Discourse","date":"2024-07-20","arxiv_id":"2407.17522","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-study-of-transfer-learning-for","title":"A Comparative Study of Transfer Learning for Emotion Recognition using CNN and Modified VGG16 Models","date":"2024-07-19","arxiv_id":"2407.14576","repositories_listed":0,"syntology":null},{"url":null,"slug":"emocam-toward-understanding-what-drives-cnn","title":"EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition","date":"2024-07-19","arxiv_id":"2407.14314","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00780","title":"In-Depth Analysis of Emotion Recognition through Knowledge-Based Large Language Models","date":"2024-07-17","arxiv_id":"2408.00780","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-facial-expression-recognition","title":"Enhancing Facial Expression Recognition through Dual-Direction Attention Mixed Feature Networks: Application to 7th ABAW Challenge","date":"2024-07-17","arxiv_id":"2407.12390","repositories_listed":0,"syntology":null},{"url":null,"slug":"pcq-emotion-recognition-in-speech-via","title":"PCQ: Emotion Recognition in Speech via Progressive Channel Querying","date":"2024-07-17","arxiv_id":"2407.12380","repositories_listed":0,"syntology":null},{"url":null,"slug":"temporal-label-hierachical-network-for","title":"Temporal Label Hierachical Network for Compound Emotion Recognition","date":"2024-07-17","arxiv_id":"2407.12973","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-vision-language-models-as-emotion","title":"Large Vision-Language Models as Emotion Recognizers in Context Awareness","date":"2024-07-16","arxiv_id":"2407.11300","repositories_listed":0,"syntology":null},{"url":null,"slug":"emotion-detection-through-body-gesture-and","title":"Emotion Detection through Body Gesture and Face","date":"2024-07-13","arxiv_id":"2407.09913","repositories_listed":0,"syntology":null},{"url":null,"slug":"pso-fuzzy-xgboost-classifier-boosted-with","title":"PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition","date":"2024-07-13","arxiv_id":"2407.09950","repositories_listed":0,"syntology":null},{"url":null,"slug":"sensemo-enabling-affective-learning-through","title":"SensEmo: Enabling Affective Learning through Real-time Emotion Recognition with Smartwatches","date":"2024-07-13","arxiv_id":"2407.09911","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-emotion-recognition-in-incomplete","title":"Enhancing Emotion Recognition in Incomplete Data: A Novel Cross-Modal Alignment, Reconstruction, and Refinement Framework","date":"2024-07-12","arxiv_id":"2407.09029","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-speech-unit-selection-for-textless","title":"Analyzing Speech Unit Selection for Textless Speech-to-Speech Translation","date":"2024-07-08","arxiv_id":"2407.18332","repositories_listed":0,"syntology":null},{"url":null,"slug":"merge-a-bimodal-dataset-for-static-music","title":"MERGE -- A Bimodal Audio-Lyrics Dataset for Static Music Emotion Recognition","date":"2024-07-08","arxiv_id":"2407.06060","repositories_listed":0,"syntology":null},{"url":null,"slug":"msp-podcast-ser-challenge-2024-l-antenne-du","title":"MSP-Podcast SER Challenge 2024: L'antenne du Ventoux Multimodal Self-Supervised Learning for Speech Emotion Recognition","date":"2024-07-08","arxiv_id":"2407.05746","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-layer-anchoring-strategy-for-enhancing","title":"A Layer-Anchoring Strategy for Enhancing Cross-Lingual Speech Emotion Recognition","date":"2024-07-06","arxiv_id":"2407.04966","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-context-aware-emotion-recognition","title":"Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Training","date":"2024-07-06","arxiv_id":"2407.04963","repositories_listed":0,"syntology":null},{"url":"/paper/real-time-emotion-analysis-using-deep","slug":"real-time-emotion-analysis-using-deep","title":"Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond","date":"2024-07-05","arxiv_id":"2407.04560","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-technology-for-human-emotion","title":"Generative Technology for Human Emotion Recognition: A Scope Review","date":"2024-07-04","arxiv_id":"2407.03640","repositories_listed":0,"syntology":null},{"url":null,"slug":"mvgt-a-multi-view-graph-transformer-based-on","title":"MVGT: A Multi-view Graph Transformer Based on Spatial Relations for EEG Emotion Recognition","date":"2024-07-03","arxiv_id":"2407.03131","repositories_listed":0,"syntology":null},{"url":null,"slug":"masontigers-at-semeval-2024-task-10-emotion","title":"MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Prompting","date":"2024-06-30","arxiv_id":"2407.00581","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-learning-for-affect-analysis","title":"Multi-Task Learning for Affect Analysis","date":"2024-06-30","arxiv_id":"2407.00679","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-generative-language-models-multicultural","title":"Are Generative Language Models Multicultural? A Study on Hausa Culture and Emotions using ChatGPT","date":"2024-06-27","arxiv_id":"2406.19504","repositories_listed":0,"syntology":null},{"url":"/paper/efficient-long-distance-latent-relation-aware","slug":"efficient-long-distance-latent-relation-aware","title":"Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations","date":"2024-06-27","arxiv_id":"2407.00119","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-emotion-recognition-under-resource","title":"Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation","date":"2024-06-21","arxiv_id":"2406.15119","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adapter-based-unified-model-for-multiple","title":"An Adapter-Based Unified Model for Multiple Spoken Language Processing Tasks","date":"2024-06-20","arxiv_id":"2406.14747","repositories_listed":0,"syntology":null},{"url":null,"slug":"apprenticeship-inspired-elegance-synergistic","title":"Apprenticeship-Inspired Elegance: Synergistic Knowledge Distillation Empowers Spiking Neural Networks for Efficient Single-Eye Emotion Recognition","date":"2024-06-20","arxiv_id":"2407.09521","repositories_listed":0,"syntology":null},{"url":null,"slug":"dasb-discrete-audio-and-speech-benchmark","title":"DASB -- Discrete Audio and Speech Benchmark","date":"2024-06-20","arxiv_id":"2406.14294","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-task-specific-subnetworks-in-multi","title":"Finding Task-specific Subnetworks in Multi-task Spoken Language Understanding Model","date":"2024-06-18","arxiv_id":"2406.12317","repositories_listed":0,"syntology":null},{"url":null,"slug":"double-multi-head-attention-multimodal-system","title":"Double Multi-Head Attention Multimodal System for Odyssey 2024 Speech Emotion Recognition Challenge","date":"2024-06-15","arxiv_id":"2406.10598","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-emotion-recognition-using-cnn-and-its","title":"Speech Emotion Recognition Using CNN and Its Use Case in Digital Healthcare","date":"2024-06-15","arxiv_id":"2406.10741","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-does-it-take-to-generalize-ser-model","title":"What Does it Take to Generalize SER Model Across Datasets? A Comprehensive Benchmark","date":"2024-06-14","arxiv_id":"2406.09933","repositories_listed":0,"syntology":null},{"url":null,"slug":"cldta-contrastive-learning-based-on-diagonal","title":"CLDTA: Contrastive Learning based on Diagonal Transformer Autoencoder for Cross-Dataset EEG Emotion Recognition","date":"2024-06-12","arxiv_id":"2406.08081","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-self-supervised-multi-view","title":"Exploring Self-Supervised Multi-view Contrastive Learning for Speech Emotion Recognition with Limited Annotations","date":"2024-06-12","arxiv_id":"2406.07900","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-language-models-for-emotion","title":"Improving Language Models for Emotion Analysis: Insights from Cognitive Science","date":"2024-06-11","arxiv_id":"2406.10265","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-emotion-recognition-based-on","title":"Multimodal Emotion Recognition based on Facial Expressions, Speech, and EEG","date":"2024-06-11","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"persona-an-application-for-emotion","title":"PERSONA: An Application for Emotion Recognition, Gender Recognition and Age Estimation","date":"2024-06-10","arxiv_id":"2406.06781","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-large-language-models-more-empathetic","title":"Are Large Language Models More Empathetic than Humans?","date":"2024-06-07","arxiv_id":"2406.05063","repositories_listed":0,"syntology":null},{"url":null,"slug":"emo-bias-a-large-scale-evaluation-of-social","title":"Emo-bias: A Large Scale Evaluation of Social Bias on Speech Emotion Recognition","date":"2024-06-07","arxiv_id":"2406.05065","repositories_listed":0,"syntology":null},{"url":null,"slug":"think-out-loud-emotion-deducing-explanation","title":"Think out Loud: Emotion Deducing Explanation in Dialogues","date":"2024-06-07","arxiv_id":"2406.04758","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-data-inconsistency-for-multi","title":"Evaluation of data inconsistency for multi-modal sentiment analysis","date":"2024-06-05","arxiv_id":"2406.03004","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-microphone-speech-emotion-recognition","title":"Multi-Microphone Speech Emotion Recognition using the Hierarchical Token-semantic Audio Transformer Architecture","date":"2024-06-05","arxiv_id":"2406.03272","repositories_listed":0,"syntology":null},{"url":null,"slug":"e-icl-enhancing-fine-grained-emotion","title":"E-ICL: Enhancing Fine-Grained Emotion Recognition through the Lens of Prototype Theory","date":"2024-06-04","arxiv_id":"2406.02642","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-qualitative-and-computational","title":"Combining Qualitative and Computational Approaches for Literary Analysis of Finnish Novels","date":"2024-06-03","arxiv_id":"2406.01021","repositories_listed":0,"syntology":null},{"url":null,"slug":"1st-place-solution-to-odyssey-emotion","title":"1st Place Solution to Odyssey Emotion Recognition Challenge Task1: Tackling Class Imbalance Problem","date":"2024-05-30","arxiv_id":"2405.20064","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-emotion-recognition-in-conversation","title":"Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning","date":"2024-05-28","arxiv_id":"2405.17900","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-thermography-technology-a","title":"Exploring Thermography Technology: A Comprehensive Facial Dataset for Face Detection, Recognition, and Emotion","date":"2024-05-28","arxiv_id":"2407.09494","repositories_listed":0,"syntology":null}],"record_sha256":"72ebfcd6779895139e358334f27ea8eb97e10a95d71ca0d90b74565db89d8e46","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}