Tuesday, June 13, 2023

Unleash Your Voice: Empowering Self-Expression through Voice Cloning

Unlock the power of your unique voice with cutting-edge voice cloning technology. Now you can effortlessly clone your own voice, capturing every nuance and tone, without relying on any specific brand or product. Dive into the realm of personalized audio expression and bring your ideas to life like never before. With our innovative voice cloning solution, your voice becomes your ultimate tool for creativity and self-expression. Discover the freedom to mold your voice in exciting ways, opening up a world of endless possibilities. Embrace the future of voice cloning and unleash your voice's true potential.

In this article, I will show how to clone your own voice. It requires knowledge of Python though but I think some websites already offer  a paid subscription that will enable you to clone your own voice.

To create a Python voice cloner program using Real-Time-Voice-Cloning (RTVC), you'll need to install the necessary libraries and follow a step-by-step process. Here's a general outline of the steps involved:

Install dependencies:

  • Install Python 3.x (if not already installed)
  • Install the required libraries by running the following commands:

pip install tensorflow==1.15
pip install numba==0.48
pip install SoundFile
pip install unidecode
pip install librosa

Clone the Real-Time-Voice-Cloning repository:

git clone https://github.com/CorentinJ/Real-Time-Voice-Cloning.git

Download the pretrained models:

  • Download the "pretrained.zip" file from the following link: https://github.com/CorentinJ/Real-Time-Voice-Cloning/releases/tag/v1.1-pretrained
  • Extract the contents of the zip file into the cloned repository folder.

Create a Python script for the voice cloner:

Import the necessary modules
import sys
import os
import numpy as np
import librosa
import argparse
from synthesizer.inference import Synthesizer
from encoder import inference as encoder
from vocoder import inference as vocoder
from pathlib import Path

Set up paths to the model files:

encoder_weights = Path("pretrained/encoder/saved_models/pretrained.pt")
vocoder_weights = Path("pretrained/vocoder/saved_models/pretrained/pretrained.pt")
syn_dir = Path("pretrained/synthesizer/saved_models/logs-pretrained/taco_pretrained")

Initialize the models:

encoder.load_model(encoder_weights)
synthesizer = Synthesizer(syn_dir)
vocoder.load_model(vocoder_weights)

Define a function for cloning the voice:

def clone_voice(input_file, output_file):

    # Load input audio
    audio, sr = librosa.load(input_file, 22050)
    # Preprocess audio
    wav = encoder.preprocess_wav(audio, sr)
    # Extract speaker embeddings
    speaker_embed = encoder.embed_utterance(wav)
    # Synthesize cloned voice
    specs = synthesizer.synthesize_spectrograms([input_text], [speaker_embed])
    generated_wav = vocoder.infer_waveform(specs[0])
    # Save synthesized audio
    librosa.output.write_wav(output_file, generated_wav, synthesize_sample_rate)

Parse command-line arguments:

parser = argparse.ArgumentParser(description="Python Voice Cloner")
parser.add_argument("--input_file", help="Path to input audio file")
parser.add_argument("--output_file", help="Path to output cloned audio file")
args = parser.parse_args()

Clone the voice:

clone_voice(args.input_file, args.output_file)

Run the Python script:

Open a terminal or command prompt and navigate to the cloned repository folder.
Execute the Python script with the appropriate command-line arguments:
python voice_cloner.py --input_file path/to/input.wav --output_file path/to/output.wav

Ensure that you have a suitable input audio file and specify the paths to the input and output files accordingly. The script will generate a cloned version of the input voice in the specified output file.

Please note that Real-Time 


Reference:



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