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:
- 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
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.