Novel to Audiobook
An automated pipeline that converts web novels into long-form audiobooks using AI-assisted text processing and text-to-speech synthesis.
Overview
Novel to Audiobook is a Python-based automation project that transforms raw web novel text into coherent, chapter-length audiobooks. The system handles text cleaning, segmentation, and narration orchestration, removing the need for manual preprocessing and voice recording.
The project focuses on building a reliable pipeline for long-form audio generation rather than short, single-prompt outputs.
Key Features
- •Automated conversion of web novels into audiobook-ready audio
- •AI-assisted text cleaning to remove noise and normalize raw content
- •Intelligent text segmentation for long-form narration
- •End-to-end orchestration from raw text to synthesized audio files
- •Support for chapter-length and multi-chapter content
Tech Stack
Frontend
None
Backend
Python, requests, beautifulsoup, tqdm, pydub
Database
PostgreSQL
DevOps & Deployment
Docker
AI & APIs
Google Cloud TTS, Google Gemini API, Google Cloud Monitoring, Google Auth
Technical Deep Dive
Raw web novel content often contains inconsistent formatting, ads, and noise that degrade narration quality
Integrated AI-assisted text preprocessing to normalize content and produce clean, TTS-ready inputs.
Generating coherent audio for long chapters without TTS limits or voice inconsistency
Implemented efficient text segmentation and orchestration to maintain narration flow across large inputs.
Ensuring the pipeline scales beyond small samples to full novels
Designed the system as a modular pipeline, allowing reliable processing of multi-chapter content.
Learning Outcomes
- ✓Gained hands-on experience designing end-to-end automation pipelines for long-form content processing, from raw text ingestion to final audio output.
- ✓Developed a deeper understanding of AI-assisted text preprocessing, including cleaning noisy real-world data and preparing inputs for downstream systems.
- ✓Learned how to segment and orchestrate long-form text-to-speech workflows, balancing API limits, audio coherence, and narration quality.
- ✓Strengthened skills in integrating cloud-based AI services (LLMs and TTS) into a reliable, repeatable production pipeline.
- ✓Improved ability to design systems that scale beyond demos, focusing on robustness, modularity, and real-world constraints.