DrewThomasson/ebook2audiobook
Ebook2audiobook
This project is a scalable, containerized pipeline designed to transform digital documents and image-based ebooks into narrated audiobooks. It functions as an end-to-end production platform that integrates text-to-speech synthesis, optical character recognition, and automated workflow management to convert various file formats into spoken audio.
The system distinguishes itself through advanced linguistic analysis and voice synthesis capabilities, including the ability to identify characters within a text and assign them distinct voice profiles for multi-speaker narration. Users can further personalize the output by training custom voice models on audio samples or by using markup tags to exert fine-grained control over pacing, pauses, and speaker switching during the generation process.
The platform supports high-volume production through parallel task orchestration and batch processing, with the option to offload resource-intensive rendering tasks to remote cloud environments or local graphics hardware. It provides both a command-line interface and a web-based dashboard to manage file uploads, voice assignments, and the lifecycle of audio generation tasks. The entire application stack is packaged into containerized environments to ensure consistent execution across diverse infrastructure.
Features
- Audiobook Converters - Transforms digital documents and scanned books into high-quality spoken audiobooks using advanced text-to-speech engines.
- Document Conversion - Transforms various ebook, document, and image-based file formats into spoken audiobooks using a selection of text-to-speech engines.
- Text-to-Speech Tools - Transforms digital documents and image-based ebooks into narrated audiobooks using advanced speech synthesis and character-based voice assignment.
- Voice Cloning Tools - Generates realistic speech from text by leveraging custom voice cloning and multi-speaker narration models for high-quality audio production.
- Voice Synthesis - Creates personalized narration by training custom speech models on audio samples to mimic specific human voices for realistic storytelling.
- Voice Cloning - Synthesizes speech using provided audio samples to create personalized narration that mimics the unique characteristics of a specific human voice.
- Workflow Automation - Provides automated workflows for batch converting documents into audiobooks with fine-grained control over narration pacing and speaker switching.
- Media Processing Pipelines - Provides a scalable architecture that packages conversion services into isolated environments to manage resource-intensive audio rendering tasks.
- Audiobook Players - Converts ebooks to audiobooks using ai voice cloning.
- Character Dialog Extraction - Analyzes book text to identify characters and attribute spoken lines to specific speakers using natural language processing techniques.
- Speech Model Fine-Tuning - Enables training custom text-to-speech models on specific voice samples to improve the quality and personalization of generated audiobook narration.
- Multi-Speaker Synthesis - Identifies characters within a text and maps their dialogue to specific voice profiles for multi-speaker narration.
- Voice Personalization - Matches identified characters to specific audio voices based on inferred age and gender traits to create realistic multi-speaker narration.
- Document Processing Tools - Extracts readable text from scanned pages and image-based files to enable audio conversion for documents that lack native digital text.
- Containerized Service Deployments - Deploys audio rendering services within containerized environments to ensure consistent performance across diverse hardware and cloud infrastructure.
- Batch Processing - Enables simultaneous conversion of multiple documents or entire folders into audio files using parallel processing.
- Cloud Execution Environments - Supports running resource-intensive audio rendering tasks within remote hosted environments to offload heavy processing requirements from local hardware.
- Optical Character Recognition - Converts image-based documents into machine-readable text by applying pattern recognition before passing the content to the speech synthesis engine.
- Speech Synthesis - Injects custom control tags into text streams to trigger precise timing, pauses, and voice switching during the audio generation process.
- Speech Emphasis Controls - Allows users to inject custom tags into text to manage pauses, silence durations, and voice switching for precise control over the final audio output.
- Document Processing and Conversion - Extracts readable text from image-based files and scanned pages to enable audio conversion for documents lacking native digital text.
- Container Isolation Technologies - Packages the entire application stack and its dependencies into standardized images to ensure consistent execution across diverse hardware and operating systems.
- Containerized Deployments - Supports packaging applications and dependencies into isolated container environments to ensure consistent execution across different hardware and operating systems.
- Distributed Task Orchestration - Distributes heavy processing workloads across multiple concurrent threads or remote nodes to maximize throughput during batch media conversion.
- GPU Acceleration - Offloads heavy text-to-audio processing tasks to dedicated graphics hardware to reduce wait times when handling large files.
