This is a machine learning project that utilizes Text-to-Speech (TTS) technology to convert EPUB books into audiobooks. The project is implemented in Jupyter Notebook, and it allows users to input EPUB files, process the text data, and generate audio output in the form of audiobooks. The project utilizes a pre-trained TTS model to generate human-like speech from the text data.

• Convert EPUB books into audiobooks.
• Utilize a pre-trained TTS model to generate speech.
• Customize audio output settings, such as voice, speed, and volume.
• Process text data, including text normalization, punctuation removal, and sentence segmentation.
• Save generated audiobooks in various audio file formats, such as WAV, MP3, or OGG.
• Visualize the text data and audio output for analysis and evaluation.
• Compatible with popular machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn.

• Python 3.7 or higher
• Jupyter Notebook
• Dependencies: [List the required dependencies and their versions]
• EPUB books for input data

1. Clone the repository to your local machine:

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git clone https://github.com/your-username/your-repo.git

2. Install the required dependencies:

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pip install -r requirements.txt

3. Download and install the pre-trained TTS model:

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# Provide instructions to download and install the pre-trained TTS model

1. Open the Jupyter Notebook:

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jupyter notebook

2. Navigate to the project directory and open the "Text_to_Speech_ML_Project.ipynb" notebook.
3. Follow the instructions in the notebook to load EPUB books, process the text data, and generate audiobooks using the TTS model.
4. Customize audio output settings, such as voice, speed, and volume, to suit your preferences.
5. Save the generated audiobooks in your desired audio file format.
6. Analyze and evaluate the audio output and text data using the provided visualization tools.

Contributions to this project are welcome! If you find any issues or have suggestions for improvement, please open an issue or submit a pull request.

This project is licensed under the MIT License.

• [List any acknowledgements, credits, or references to external sources that were used in the project]

For any questions, comments, or inquiries, please contact [Your Name] at [Your Email Address].