emotion-recognition-conversations
importeddata/emotion-recognition-conversations
Diploma thesis analyzing emotion recognition in conversations exploiting physiological signals (ECG, HRV, GSR, TEMP) and an Attention-based LSTM network
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Documentation
- unknown
- Tags
- affective-computing · attention-mechanism · ecg · eda · emotion-recognition · emotion-recognition-in-conversation · kemocon-dataset · lstm-model
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- AI-NLP-Paper-Readingsaffective-computing · emotion-recognition
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
- bipolar-disorderaffective-computing
Multimodal Deep Learning Framework for Mental Disorder Recognition @ FG'20
- BIOBSSecg · eda
A package for processing signals recorded using wearable sensors, such as Electrocardiogram (ECG), Photoplethysmogram (PPG), Electrodermal activity (EDA) and 3-axis acceleration (ACC).
- Emo_Phys_Evalecg · emotion-recognition
Repository for "Inter and Intra Signal Variance in Feature Extraction and Classification of Affective State" AICS 2022
- Nervous-Analyticsecg · eda
Package implementing modular processes for real-time feature localization on ECG and EDA signals.
- Nervous-Sensorsecg · eda
A Python package for connecting to the Nervous ECG and EDA sensors
- api.github.com/repos/sotirismos/emotion-recognition-conversationsretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2022-09-11, 29 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/41.json→ .entries["emotion-recognition-conversations"]
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