Voice-Cloning-Project

Introduction

This project aims to perform voice cloning and translation tasks using Python. It utilizes various libraries and techniques to achieve the following objectives:

Here my input is string (example: sharukhan tedx, samanatha tedx)

1.YouTube Video Extraction: The project starts by searching for YouTube videos related to a specific keyword using the YouTube Data API. It extracts video links for further processing.

2.Video Download and Audio Extraction: It downloads the YouTube videos and extracts the audio content from them. The extracted audio is saved as WAV files.

3.Audio Segmentation: The audio files are split into smaller segments to process them individually. This segmentation helps in handling longer audio recordings efficiently.

4.Speech Recognition: Using the SpeechRecognition library, the project converts audio segments into text. This step enables the system to work with spoken content.

5.Translation: The extracted text is translated into multiple languages. In this project, translations to Telugu and Hindi are demonstrated using the Google Translate API.

6.Voice Cloning: Custom voice cloning is performed using the Tortoise library. It generates speech in multiple languages with the voice of the user's choice.

Note:

You should keep all the voice_segment files in Voice_Clone with tortoise-tts.ipynb where voice_segments are act as a dataset and u get the voice segment by executing the main.py

Project Structure

The project is structured as follows:

• 'main.py': The main script that orchestrates the entire process, from video extraction to voice cloning.
• 'audio_processing.py': Contains functions for audio extraction and segmentation.
• 'translation.py': Handles text translation to Telugu and Hindi.
• 'Voice_Clone with tortoise-tts.ipynb': Manages the custom voice cloning process.
• 'videos_dir/': Directory to store downloaded YouTube videos.
• 'voice_wav/': Directory to store extracted audio in WAV format.
• 'voice_segments/': Directory to store segmented audio clips.
• 'tortoise': Contains custom voice models and related data.

Getting Started

1.Clone the repository to your local machine.

2.Install the required Python libraries listed in the 'requirements.txt' file.

3.Obtain a 'YouTube Data API' key from the Google Developer Console and replace the api_key variable in 'main.py' with your key.

4.Run 'main.py' to execute the entire voice cloning and translation pipeline.

Dependencies

• Python 3.x
• Google YouTube Data API
• Tortoise Voice Cloning Library
• SpeechRecognition Library
• Pytube Library
• Googletrans Library
• MoviePy Library
• NumPy Library

Recorded Video

Final_Output.mp4