| Amir Singh Model - Indian "Über Eats" Typ Voice Clone | |
| # Amir Singh Model - Indian "Über Eats" Typ Voice Clone | |
| ## Overview | |
| The **Amir Singh Model** is a voice cloning model trained to mimic the voice of an "Indian Über Eats Typ". It uses RVC (Retrieval-based Voice Conversion) technology for efficient and accurate voice synthesis. The model was developed and trained on minimal data and optimized for quick deployment and use. | |
| **He is built different** | |
| ## Key Features | |
| * **Voice Type**: Indian Über Eats Typ (Amir Singh) | |
| * **Training Data**: 5 minutes of audio data | |
| * **Epochs**: 250 epochs | |
| * **Segmentation & Training**: | |
| * Data segmentation: 5 hours | |
| * Training time: 1 hour | |
| * **Hardware Used**: | |
| * GPU: NVIDIA RTX 4060 TI (8GB VRAM) | |
| * RAM: 24GB | |
| ## About RVC (Retrieval-based Voice Conversion) | |
| RVC is a cutting-edge technology designed for voice conversion and cloning. It employs a retrieval-based approach that ensures the generated voice closely resembles the target voice with minimal artifacts. RVC is highly efficient, making it suitable for training with limited data while delivering high-quality results. | |
| ### Why RVC? | |
| * **Low Data Requirement**: High-quality voice models can be created with as little as a few minutes of training data. | |
| * **Fast Training**: Optimized for quick model training and deployment. | |
| * **High Fidelity**: Produces realistic and natural-sounding voice outputs. | |
| ## Model Specifications | |
| * **Input**: Audio samples for training (5 minutes) | |
| * **Output**: Synthetic voice resembling "Amir Singh" with high accuracy | |
| * **Performance**: Designed to work efficiently on systems with moderate hardware capabilities | |
| ## Usage | |
| To use the Amir Singh Model: | |
| 1. Install the necessary dependencies, including RVC. | |
| 2. Load the trained model in your preferred framework or platform. | |
| 3. Input text or audio for voice conversion or synthesis. | |
| 4. Generate outputs that replicate the Amir Singh voice | |
| Overview | |
| The Amir Singh Model is a voice cloning model trained to mimic the voice of an "Indian Über Eats Typ". It uses RVC (Retrieval-based Voice Conversion) technology for efficient and accurate voice synthesis. The model was developed and trained on minimal data and optimized for quick deployment and use. | |
| Key Features | |
| Voice Type: Indian Über Eats Typ (Amir Singh) | |
| Training Data: 5 minutes of audio data | |
| Epochs: 250 epochs | |
| Segmentation & Training: | |
| Data segmentation: 5 hours | |
| Training time: 1 hour | |
| Hardware Used: | |
| GPU: NVIDIA RTX 4060 TI (8GB VRAM) | |
| RAM: 24GB | |
| About RVC (Retrieval-based Voice Conversion) | |
| RVC is a cutting-edge technology designed for voice conversion and cloning. It employs a retrieval-based approach that ensures the generated voice closely resembles the target voice with minimal artifacts. RVC is highly efficient, making it suitable for training with limited data while delivering high-quality results. | |
| Why RVC? | |
| Low Data Requirement: High-quality voice models can be created with as little as a few minutes of training data. | |
| Fast Training: Optimized for quick model training and deployment. | |
| High Fidelity: Produces realistic and natural-sounding voice outputs. | |
| Model Specifications | |
| Input: Audio samples for training (5 minutes) | |
| Output: Synthetic voice resembling "Amir Singh" with high accuracy | |
| Performance: Designed to work efficiently on systems with moderate hardware capabilities | |
| Usage | |
| To use the Amir Singh Model: | |
| Install the necessary dependencies, including RVC. | |
| Load the trained model in your preferred framework or platform. | |
| Input text or audio for voice conversion or synthesis. | |
| Generate outputs that replicate the Amir Singh voice. | |