Tag
#speech-to-text
Speaker Diarization Privacy Tradeoffs: When Labels Become Identifiers
I've seen diarization labels re-identify speakers in HIPAA calls. Here's when speaker IDs become PHI, and when to disable diarization in your transcription pipeline.
Speech-to-Text SLAs: Uptime, Latency Targets, and What Breaks First
Uptime badges hide concurrency cliffs and regional latency. I've mapped what speech-to-text SLAs really cover and what to load-test before you sign a vendor contract.
Your Deepgram Voice Agent Pilot Just Got 34% More Expensive: Unbundle STT Before Sept 13
Deepgram's Voice Agent promo ends Sept 12 — Standard jumps 34% on Sept 13. I've mapped the tier math and three migration paths, including unbundling STT with Pipecat.
Speech-to-Text for Knowledge Base Ingestion: From Calls to Searchable Docs
I've wired call recordings into searchable knowledge bases for four B2B teams. This guide covers the ingest pipeline: preprocessing, Agent-mode transcription, metadata, dedupe, and chunk tuning for RAG-ready content.
Agent-Mode Transcription for RAG Pipelines: Fewer Tokens, Cleaner Chunks
Agent-mode transcription for RAG pipelines shrinks filler before chunking. I've measured 35-50% fewer tokens vs Raw, cleaner retrieval, and lower embed cost.
Speech-to-Text for Incident Response Recordings: Chain of Custody Without Public APIs
I've sat on IR bridges where war-room audio got dropped into a public Whisper API for searchable notes. That habit breaks chain of custody. Here's the private transcription pattern I use when recordings may become evidence.
Zero-Retention Transcription APIs: What 'No Training' Actually Guarantees
No training is not zero retention. I break down OpenAI, Deepgram, and AssemblyAI retention defaults, then the DPA language and retrieve-after-N-minutes test I require before production audio leaves the VPC.
Transcription Billing Surprises Finance Teams Catch Too Late
Finance sees transcription billing surprises weeks after engineering ships voice. I've reconciled invoices where rounding, add-ons, streaming premiums, and free-tier cliffs blew the forecast.
Speech-to-Text Budget Forecasting: How to Predict Monthly Transcription Spend
Finance teams get blindsided by transcription invoices when forecasts ignore rounding, spikes, and feature add-ons. Here's the forecasting model I use before signing any STT contract.
PII Redaction in Speech-to-Text: What Works in Production Pipelines
I've wired PII redaction into call and agent transcription stacks. Transcript NER alone is not enough. Here's the production stack that holds up under audit.
Transcription Confidence Scores: When to Trust Them (and When to Ignore Them)
I've watched production teams treat transcription confidence scores like a truth meter. Here's what those numbers measure, when to trust them, and how agents should fall back.
Voice Activity Detection Before Transcription: Cut Silence, Cost, and Latency
I've deployed VAD in production transcription pipelines. Here's how to cut silence before STT and lower cost and latency without hurting transcript accuracy.
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