Audio and podcasting decision
SpeechReader
A competent developer can reproduce the core TTS features (paste/upload → OCR → synthesize → download) in ~36 hours using existing OSS TTS and OCR projects; the vendor's main durable advantage is brand trust and a large curated voice catalogue you would not match immediately.
Visit website↗$6/mo
$72/yr
Read off the official pricing page.
$100one-off36 h to build
$25/mo3 h/mo upkeep
On cash alone, building overtakes the subscription at 6 seats.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- Accept text or uploaded PDF/image -> extract text (OCR) -> synthesize audio via TTS model/API -> provide playback and MP3 download.
What it still won’t have
- Polished multi-voice catalogue (1000+ voices) and voice marketplace
- Priority support and commercial SLA
- Branded web UX and instant free tier onboarding
- Any proprietary voice models or optimizations maintained by vendor
What remains hard
- Brand trust
Trusted by thousands for reading, learning, and accessibility.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 6 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 web app (React frontend + Node/Express backend) that lets a user paste text or upload a PDF/image, extracts text with Tesseract (or Google Vision), sends text to an open-source TTS model (Coqui TTS) or Google Cloud TTS, encodes output to MP3, stores files in S3, and returns downloadable audio. In scope: paste/upload UI, OCR pipeline, TTS integration, job queue for long conversions, MP3 generation, simple auth for a single user, deployment scripts (Docker + single VPS), logging, error handling, and unit/integration tests. Out of scope: multi-tenant billing system, large-scale voice catalogue UI, commercial support SLA, and training custom voice models.
How we checked
How the score was reached
- Build verdict base78
- 2 cited sources+1
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score86
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 · 2
Every page the run actually retrieved.
- official productSpeechReader — product
- official pricingSpeechReader — pricing
Integrity checks
What held up, and what did not.
