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From call audio to CSAT: Mapping contact center sentiment to CX signals
TL;DR: Manual QA teams sample 2–5% of contact center calls, leaving more than 95% of customer interactions unscored. Transcript errors propagate directly into your sentiment layer: a single substitution that flips "can't" to "can" inverts the sentiment signal before your classifier runs, making transcription quality a direct input to CSAT reliability. To automate quality assurance at 100% coverage, solve the transcription layer first. This playbook maps the audio-to-CSAT pipeline, explains where transcript errors compound into false QA scores, and shows the four production steps required to scale sentiment analysis across noisy, multilingual Business Process Outsourcing (BPO) environments.
Integrating speech-to-text into your EHR: epic, athenahealth and FHIR
TL;DR: The real engineering work in EHR speech integration is mapping unstructured audio payloads to the correct FHIR resources, managing SMART on FHIR OAuth 2.0, and building resilient async write pipelines that survive rate limits and EHR downtime. On Growth and Enterprise plans, customer data is never used for model training, which is an important baseline control for any clinical pipeline handling PHI. The architectural patterns in this guide apply whether you choose a managed STT API or build the transcription layer yourself.
European-language speech-to-text: evaluating coverage and accuracy
TL;DR: Academic benchmarks fail to predict production STT performance in European business environments, where accented speech, code-switching, and telephony noise push real-world Word Error Rate well above what clean read-speech datasets suggest. Engineering and ML Leads evaluating STT infrastructure need three metrics standard benchmarks don't capture: real-world WER on accented audio, Language Adherence Violation Rate for code-switching performance, and total cost of ownership (TCO) including engineering toil for self-hosted GPU clusters. On Switchboard, the most demanding conversational telephone dataset, Solaria-3 ranks #1 ahead of AssemblyAI, ElevenLabs, Deepgram, Mistral, and Speechmatics: a concrete example of how production-relevant benchmarking changes the vendor picture. This guide provides the technical framework to run a statistically valid evaluation against your own audio distribution before committing to any vendor or build decision.
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
From call audio to CSAT: mapping contact center sentiment to CX signals
Speech-To-Text
Integrating speech-to-text into your EHR: Epic, athenahealth and FHIR
Speech-To-Text
European-language speech-to-text: evaluating coverage and accuracy
From audio to knowledge
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