Audio and podcasting decision
VoiceCheap
A competent technical user can reproduce the core dubbing pipeline (transcribe → translate → TTS/lip-sync → export) using existing open-source projects and APIs within a multi-week build; the vendor's hosted polish, voice catalog, and enterprise features are the primary reasons to keep paying.
Visit website↗$7/mo
$84/yr
Read off the official pricing page.
$100one-off52 h to build
$200/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 30 seats.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All VoiceCheap alternatives, with the arithmetic →
What a replacement has to do
- Upload video → transcribe source audio → translate transcript → synthesize dubbed audio (voice/TTS/clone) with lip-sync → merge audio into video and export
What it still won’t have
- Access to a large curated voice library and production-ready voice clones
- Polished UI/UX and scheduling/publishing integrations
- Enterprise features (team seats, brand dictionary, built-in API ergonomics)
- Scale and reliability of a hosted SaaS (auto-scaling encoding, edge delivery)
- Commercial support and SLAs
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 30 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal AI video dubbing service in Node.js (Express) + React for UI, Postgres for metadata, and S3-compatible storage. Core features in scope: authenticated single-user upload, background worker that (1) sends audio to a speech-to-text API and stores timestamped transcript, (2) sends transcript to a translation API with support for a simple glossary, (3) sends translated text to a TTS API (or open-source TTS) and runs a lip-sync alignment step to produce a synced audio track, (4) muxes the dubbed audio into the original video and provides an MP4 export and SRT subtitle file. Out of scope: multi-tenant billing, team collaboration, brand dictionary UI, advanced voice-cloning training. Include retry/error handling for all external calls, end-to-end tests for the pipeline, logging and basic metrics, and Dockerfiles for deployment.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 4 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score67
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 4
Every page the run actually retrieved.
- official productVoiceCheap | AI Video Dubbing & Translation Platform
- official docsVoiceCheap Documentation — Introduction
- open sourceHuanshere/VideoLingo
- open sourcebuxuku/SmartSub
Integrity checks
What held up, and what did not.
