# rushil07pawar/speech-emotion-recogntion-using-mfcc architecture

> Architecture diagram of the GitHub repository rushil07pawar/speech-emotion-recogntion-using-mfcc, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-29). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/rushil07pawar/speech-emotion-recogntion-using-mfcc
- Repository: https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc

## Overview

This notebook-based Speech Emotion Recognition project takes English or Hindi audio datasets through feature extraction and model training, then offers emotion prediction through a Gradio interface. The README documents dataset downloading, augmentation, CNN/BiLSTM/SVM modeling, saved models, and interface capabilities; no notebook source was available to verify finer-grained calls or the exact wiring among those models.

Main entry points: [`Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb) (Model Training)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_data["Data and Features"]
  node_english[("English Datasets")]
  node_hindi[("Hindi Dataset")]
  node_augmentation["Audio Augmentation"]
  node_features["Audio Features"]
end

subgraph group_models["Model Training"]
  node_training["Model Training"]
  node_trained_models[("Trained Models")]
end

subgraph group_app["Prediction Interface"]
  node_interface["Gradio Interface"]
  node_audio["Audio Input"]
  node_inference["Emotion Prediction"]
  node_results["Waveform and Probabilities"]
end

node_researcher(("Researcher"))
node_kagglehub["KaggleHub"]
node_drive["Google Drive"]

node_researcher -->|"uses"| node_interface
node_kagglehub -.->|"downloads"| node_english
node_drive -.->|"stores"| node_hindi
node_english -->|"provides data"| node_training
node_hindi -->|"provides data"| node_training
node_training -->|"applies augmentation"| node_augmentation
node_training -->|"extracts features"| node_features
node_training -->|"saves models"| node_trained_models
node_audio -->|"uploaded or recorded"| node_interface
node_interface -->|"requests prediction"| node_inference
node_interface -->|"selects split"| node_trained_models
node_interface -->|"displays"| node_results

click node_english "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_hindi "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_augmentation "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_features "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_training "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_trained_models "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_interface "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_inference "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"
click node_results "https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb"

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_english,node_hindi,node_augmentation,node_features toneBlue
class node_training,node_trained_models toneAmber
class node_interface,node_audio,node_inference,node_results toneMint
class node_researcher,node_kagglehub,node_drive toneIndigo
```

## Components

### Data and Features

- [English Datasets](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`
- [Hindi Dataset](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`
- [Audio Augmentation](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`
- [Audio Features](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`

### Model Training

- [Model Training](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`
- [Trained Models](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`

### Prediction Interface

- [Gradio Interface](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`
- **Audio Input**
- [Emotion Prediction](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`
- [Waveform and Probabilities](https://github.com/rushil07pawar/speech-emotion-recogntion-using-mfcc/blob/main/Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb): `Speech_Emotion_Recognition_Using_Mfcc_SVM_and_CNN.ipynb`

### Other components

- **Researcher**
- **KaggleHub**
- **Google Drive**

## Connections

- Researcher → Gradio Interface: uses
- KaggleHub → English Datasets: downloads
- Google Drive → Hindi Dataset: stores
- English Datasets → Model Training: provides data
- Hindi Dataset → Model Training: provides data
- Model Training → Audio Augmentation: applies augmentation
- Model Training → Audio Features: extracts features
- Model Training → Trained Models: saves models
- Audio Input → Gradio Interface: uploaded or recorded
- Gradio Interface → Emotion Prediction: requests prediction
- Gradio Interface → Trained Models: selects split
- Gradio Interface → Waveform and Probabilities: displays