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.
