# sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition architecture

> Architecture diagram of the GitHub repository sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-28). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition
- Repository: https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition

## Overview

This repository is an experimental emotion-recognition project: SEED-V data is prepared and segmented, then evaluated with DNN, LSTM, CNN, and CNN-LSTM models under zero- or average-padding variants. The experiment notebooks use K-fold evaluation, and the README summarizes model and padding performance. The notebook contents were not sampled, so the graph follows the documented workflow and notebook names; it does not infer implementation-level calls or data wiring.

Main entry points: [`Data_Preprocessing_and_Segmentation.ipynb`](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Data_Preprocessing_and_Segmentation.ipynb) (Preprocessing and Segmentation), [`README.md`](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/README.md) (Reported Findings), [`Experiments/1. Zero padding Kfold DNN.ipynb`](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/1.%20Zero%20padding%20Kfold%20DNN.ipynb) (DNN Zero Padding), [`Experiments/2. Average Pooling Kfold DNN.ipynb`](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/2.%20Average%20Pooling%20Kfold%20DNN.ipynb) (DNN Average Padding)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_preparation["Data Preparation"]
  node_preprocess["Preprocessing and Segmentation"]
end

subgraph group_experiments["Model Experiments"]
  node_dnn_zero["DNN Zero Padding"]
  node_dnn_average["DNN Average Padding"]
  node_lstm_zero["LSTM Zero Padding"]
  node_lstm_average["LSTM Average Padding"]
  node_cnn_zero["CNN Zero Padding"]
  node_cnn_average["CNN Average Padding"]
  node_hybrid_average["CNN-LSTM Average Padding"]
end

subgraph group_results["Evaluation Results"]
  node_findings["Reported Findings<br/>[README.md]"]
end

node_seedv[("SEED-V Dataset")]

node_seedv -->|"provides data"| node_preprocess
node_preprocess -->|"prepares data"| node_dnn_zero
node_preprocess -->|"prepares data"| node_dnn_average
node_preprocess -->|"prepares data"| node_lstm_zero
node_preprocess -->|"prepares data"| node_lstm_average
node_preprocess -->|"prepares data"| node_cnn_zero
node_preprocess -->|"prepares data"| node_cnn_average
node_preprocess -->|"prepares data"| node_hybrid_average
node_dnn_zero -->|"reports metrics"| node_findings
node_dnn_average -->|"reports metrics"| node_findings
node_lstm_zero -->|"reports metrics"| node_findings
node_lstm_average -->|"reports metrics"| node_findings
node_cnn_zero -->|"reports metrics"| node_findings
node_cnn_average -->|"reports metrics"| node_findings
node_hybrid_average -->|"reports metrics"| node_findings

click node_preprocess "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Data_Preprocessing_and_Segmentation.ipynb"
click node_dnn_zero "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/1.%20Zero%20padding%20Kfold%20DNN.ipynb"
click node_dnn_average "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/2.%20Average%20Pooling%20Kfold%20DNN.ipynb"
click node_lstm_zero "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/3.%20Zero%20Padding%20Kfold%20LSTM.ipynb"
click node_lstm_average "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/4.%20Average%20Pooling%20Kfold%20LSTM.ipynb"
click node_cnn_zero "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/5.%20Zero%20padding%20Kfold%20CNN.ipynb"
click node_cnn_average "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/6.%20Average%20pooling%20Kfold%20CNN.ipynb"
click node_hybrid_average "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/7.%20Average%20Pooling%20Hybrid%20CNN-LSTM.ipynb"
click node_findings "https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/README.md"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_preprocess toneBlue
class node_dnn_zero,node_dnn_average,node_lstm_zero,node_lstm_average,node_cnn_zero,node_cnn_average,node_hybrid_average,node_seedv toneAmber
class node_findings toneMint
```

## Components

### Data Preparation

- [Preprocessing and Segmentation](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Data_Preprocessing_and_Segmentation.ipynb): `Data_Preprocessing_and_Segmentation.ipynb`

### Model Experiments

- [DNN Zero Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/1.%20Zero%20padding%20Kfold%20DNN.ipynb): `Experiments/1. Zero padding Kfold DNN.ipynb`
- [DNN Average Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/2.%20Average%20Pooling%20Kfold%20DNN.ipynb): `Experiments/2. Average Pooling Kfold DNN.ipynb`
- [LSTM Zero Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/3.%20Zero%20Padding%20Kfold%20LSTM.ipynb): `Experiments/3. Zero Padding Kfold LSTM.ipynb`
- [LSTM Average Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/4.%20Average%20Pooling%20Kfold%20LSTM.ipynb): `Experiments/4. Average Pooling Kfold LSTM.ipynb`
- [CNN Zero Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/5.%20Zero%20padding%20Kfold%20CNN.ipynb): `Experiments/5. Zero padding Kfold CNN.ipynb`
- [CNN Average Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/6.%20Average%20pooling%20Kfold%20CNN.ipynb): `Experiments/6. Average pooling Kfold CNN.ipynb`
- [CNN-LSTM Average Padding](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/Experiments/7.%20Average%20Pooling%20Hybrid%20CNN-LSTM.ipynb): `Experiments/7. Average Pooling Hybrid CNN-LSTM.ipynb`

### Evaluation Results

- [Reported Findings](https://github.com/sifatahammed/analysis-of-deep-learning-models-for-emotion-recognition/blob/main/README.md): `README.md`

### Other components

- **SEED-V Dataset**

## Connections

- SEED-V Dataset → Preprocessing and Segmentation: provides data
- Preprocessing and Segmentation → DNN Zero Padding: prepares data
- Preprocessing and Segmentation → DNN Average Padding: prepares data
- Preprocessing and Segmentation → LSTM Zero Padding: prepares data
- Preprocessing and Segmentation → LSTM Average Padding: prepares data
- Preprocessing and Segmentation → CNN Zero Padding: prepares data
- Preprocessing and Segmentation → CNN Average Padding: prepares data
- Preprocessing and Segmentation → CNN-LSTM Average Padding: prepares data
- DNN Zero Padding → Reported Findings: reports metrics
- DNN Average Padding → Reported Findings: reports metrics
- LSTM Zero Padding → Reported Findings: reports metrics
- LSTM Average Padding → Reported Findings: reports metrics
- CNN Zero Padding → Reported Findings: reports metrics
- CNN Average Padding → Reported Findings: reports metrics
- CNN-LSTM Average Padding → Reported Findings: reports metrics