AIAny
AI Audio2024
GitHub

ebook2audiobook

Converts e-books (epub, pdf, mobi, docx, and more) into chapter-aware audiobooks, with optional zero-shot voice cloning. Bundles eight TTS engines including XTTSv2 and Bark, and covers 1,158 languages via Meta's MMS — all runnable on CPU or GPU.

Introduction

Most text-to-speech tools make you trade reach for quality: commercial voices sound great but cover a dozen languages, while open models cover more but need glue code to handle a real book. The interesting move here is treating the TTS engine as a swappable backend — eight of them, from XTTSv2 and Bark to Meta's Fairseq/MMS — so one epub can be narrated in a cloned voice or in any of 1,158 languages without changing the workflow.

What Sets It Apart
  • Engine choice is a feature, not a fork: XTTSv2, Bark, Fairseq, VITS, Tortoise, Tacotron2, GlowTTS, and YourTTS sit behind one interface, so you match voice quality, speed, and language to the book instead of bending the book to the tool.
  • Zero-shot voice cloning from a short reference clip, with optional XTTSv2 fine-tuning when you want one consistent narrator across a whole series.
  • Real book plumbing, not just a TTS demo: it ingests 20+ formats (epub, mobi, azw3, pdf, docx, even OCR'd images) and emits chapter-aware m4b/mp3/flac — the part most "read this text aloud" scripts skip.
  • Runs almost anywhere: a 2 GB RAM / 1 GB VRAM floor, CPU or CUDA/ROCm/MPS/XPU/Jetson, driven from a Gradio web UI or a headless CLI in Docker/Podman.
Who It's For

Great fit if you want self-hosted, offline audiobook generation — especially in an uncommon language — or a consistent cloned narrator, and you don't mind tuning engines and settings. Look elsewhere if you expect one-click, broadcast-grade narration with zero setup: the eight-engine flexibility means quality varies by engine and language, and the best results take experimentation, GPU time, and patience with large model downloads.

Information

  • Websitegithub.com
  • AuthorsDrew Thomasson
  • Published date2024/01/23

Categories

More Items

Hugging Face
AI Audio2026

Generates directed, multi-character, long-form speech from text with natural-language directions and voice cloning. Built on a 35B MoE backbone (3B active per token) with a codebook multi-token-prediction decoder to enable multi-turn revision, infilling edits, streaming, and expressive control.

GitHub
AI Audio2025

Generates full songs from lyrics and style prompts by first writing an editable melody-and-chord score and then rendering vocals and accompaniment. Unifies symbolic planning and audio synthesis in one pipeline, enabling readable score inspection, zero‑shot covers, and agent-driven editing.

Hugging Face
AI Audio2026

On-device speech-to-text for short clips (up to 30s) in seven languages, yielding transcripts, word-level timestamps and per-frame speech embeddings in a single 16.9 MB model. Runs on the Needle CPU engine with 2–4 bit quantization, supports keyword biasing and returns empty transcripts for silence.