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Speech-to-text for AI medical scribes: Why clinical vocabulary breaks generic STT
TL;DR: Generic STT engines fail in clinical environments because language model probability overrides correct acoustic detection of medical terms, substituting phonetically plausible but clinically wrong candidates silently. The result corrupts drug names, dosages, and diagnoses before the LLM ever sees them. Before selecting an STT engine for a medical scribe, verify four things: whether vocabulary biasing works at inference time without fine-tuning, whether async diarization accurately separates clinician and patient audio, whether the model holds up on noisy consultation recordings rather than clean read-speech, and whether the vendor's data training policy covers PHI by default on your plan.
Migrating from self-hosted Whisper to a managed speech-to-text API
TL;DR: Self-hosting Whisper's true cost rarely sits in the model weights. GPU idle time, VRAM leaks under parallel load, and the engineering hours spent maintaining CUDA dependencies and diarization pipelines are where the bill compounds. For teams processing under roughly 3,000 hours per month, assuming 20% of one US FTE at $150K loaded annual cost, a managed API is cheaper, though the break-even shifts materially against your actual labor cost. Above that threshold, the decision depends on your DevOps overhead and whether audio accuracy on real-world recordings matters for downstream systems like CRM sync and coaching scores.
Migrating from AssemblyAI to Gladia: A step-by-step switching guide
TL;DR: Switching from AssemblyAI requires four concrete changes: update one auth header, remap batch endpoints, adjust the JSON response schema, and resample audio for WebSocket connections. Multiple customers independently report completing these in under a day with a rollback abstraction layer in place. The bigger structural difference is cost model: a production stack with diarization, sentiment, entities, and summarization runs $0.30/hr on AssemblyAI's Universal-2 tier because each feature is metered separately, versus a bundled base rate. This guide covers the exact parameter mappings, payload diffs, WebSocket reconfiguration, and a zero-downtime cutover strategy.
How to integrate live transcription API with Twilio to transcribe calls in real time
Published on Sep 28, 2023
Twilio, used by hundreds of thousands of businesses and more than ten million developers worldwide, can now integrate with our live transcription API. The integration makes it easier for users to natively transcribe any phone call in real time while using Twilio. With transcribed text at your disposal, you'll then be able to analyze, archive, and act upon voice data more effectively.
Below, you’ll find a step-by-step guide on setting up the Twilio integration with Gladia API in JavaScript for free.
What can you do with Twilio integration?
Any developer can use this integration to transcribe phone calls in real-time.
How to implement Twilio + Gladia real-time transcription integration
Step 1: Set up your Gladia account
If you haven't already, sign up for our Speech-to-Text API at app.gladia.io and obtain your API key.
Step 2: Create and parametrize your Twilio account
Get a phone number, following the first step of the main page to connect to your Twilio account.
On the left panel Develop > United States (US1) > Phone Numbers > Manage > Active numbers.
Click on the phone number you just created.
In 'Configure' panel, 'Voice Configuration' section, 'A call comes in' field, choose 'Webhook' with URL = 'http://[your-id-address]:[your-app-port-number]' and HTTP = 'HTTP POST'
Step 3: Configure your server and install dependencies
In .env file, add GLADIA_API_KEY var with your API key obtained from Gladia’s website and PORT var, the port you used to configure your phone number in above section (default is 8080)
Feel free to check out the video version of the tutorial for a step-by-step walkthrough with one of our software engineers, Antoine.
We hope you enjoyed this how-to tutorial! Given how much audio data still goes to wasted, we’re always curious to explore the many ways in which transcription tech can be used to remedy that. Let us know if you end up using our API with Twilio, Discord, or other, we’d love to hear from you.
About Gladia
At Gladia, we built an optimized version of Whisper in the form of an API, adapted to real-life professional use cases and distinguished by exceptional accuracy, speed, extended multilingual capabilities and state-of-the-art features, including speaker diarization and word-level timestamps.
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Speech-To-Text
Medical speech-to-text for AI scribe builders
Speech-To-Text
Migrating from self-hosted Whisper to a managed speech-to-text API
Speech-To-Text
AssemblyAI to Gladia migration guide: API mapping & setup
From audio to knowledge
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