Speech-to-Text APIs
How do I use Gladia to transcribe Twilio/SIP calls (8kHz) in real time?
6 min read
Quick Answer: Connect your Twilio/SIP audio stream (8 kHz) to Gladia’s real-time WebSocket API, send raw audio frames as they arrive, and consume live partial/final transcripts with word-level timestamps and diarization in under 300 ms.
Frequently Asked Questions
How do I connect Twilio/SIP 8 kHz audio to Gladia in real time?
Short Answer: Use Twilio’s media streaming (or your SIP media gateway) to forward 8 kHz mono audio over WebSocket to Gladia’s real-time transcription endpoint, then read the streamed transcript events.
Expanded Explanation:
For Twilio Voice, you enable <Start><Stream> in your TwiML so Twilio sends the call audio to your WebSocket server. That server becomes the “bridge”: it receives 8 kHz µ-law or PCM frames from Twilio/SIP, optionally normalizes them, and forwards them over another WebSocket to Gladia’s real-time API. Gladia returns low-latency partial and final transcripts you can push back into your product—agent assist, live notes, or real-time analytics.
On the SIP side (Asterisk/FreeSWITCH/CPaaS), you follow the same pattern: tap into the RTP or media gateway, stream the 8 kHz audio frames via WebSocket, and keep a 1:1 mapping between a call leg and a Gladia streaming session. The key is to keep the stream open for the whole call and send small, steady chunks.
Key Takeaways:
- Twilio sends raw media to your WebSocket; your server forwards audio to Gladia via WebSocket.
- Maintain one persistent Gladia streaming session per call for continuous real-time transcription.
What are the exact steps to set up real-time Twilio/SIP transcription with Gladia?
Short Answer: Set up Twilio/SIP media streaming, build a small WebSocket bridge server, connect that server to Gladia’s real-time API, then route transcript events into your app or CCaaS stack.
Expanded Explanation:
The integration is essentially three hops: phone call → Twilio/SIP media stream → your WebSocket bridge → Gladia. On connect, you create a Gladia streaming session with the proper parameters (8 kHz, language auto-detect, diarization, etc.). As you receive audio frames, you forward them to Gladia. Gladia responds with JSON messages containing partial and final transcripts, word-level timestamps, and optionally speaker labels. You can attach these to your agent desktop, push to your CRM, or feed an agent-assist engine in real time.
Gladia is designed to handle telephony constraints (8 kHz, SIP jitter, packet loss) without the “demo-only” assumptions of clean, 16 kHz studio audio, so you don’t need heavy preprocessing—just pass through the stream with correct encoding.
Steps:
- Enable media streaming in Twilio or SIP stack
- Twilio: add
<Start><Stream url="wss://your-bridge.example.com/twilio" />in your TwiML. - SIP: configure Asterisk/FreeSWITCH/media gateway to forward RTP/audio frames to your WebSocket bridge.
- Twilio: add
- Implement a WebSocket bridge server
- Accept WebSocket connections from Twilio/SIP.
- On new call, open a WebSocket connection to Gladia’s real-time streaming endpoint using your API key and stream parameters.
- Stream audio and consume transcripts
- Forward audio chunks as binary frames to Gladia as they arrive.
- Listen to Gladia’s transcript events (partial + final) and send them to your product (UI, agent assist, analytics, or storage).
What’s the difference between using Gladia vs. Twilio’s built-in transcription or self-hosted models for 8 kHz calls?
Short Answer: Twilio’s built-in or self-hosted models work, but Gladia is optimized for noisy 8 kHz SIP audio, multilingual conversations, and stable latency, with one API for real-time + async and add-ons like diarization, NER, and summarization.
Expanded Explanation:
Using Twilio’s built-in transcription is convenient but often struggles on real-world contact center audio: crosstalk, heavy accents, and low-bandwidth 8 kHz lines. Self-hosting Whisper or similar models gives you control, but you inherit GPU scheduling, scaling, and latency regressions—especially at volume.
Gladia is designed as a speech backbone for exactly these 8 kHz telephony and SIP use cases. It offers sub-300 ms latency, robust diarization, and strong multilingual performance, plus add-ons like custom vocabulary and entity extraction. You get one surface (REST/WebSocket) spanning real-time and batch, which simplifies your pipeline: same engine for live assist, post-call QA, and CRM enrichment.
Comparison Snapshot:
- Option A: Gladia real-time STT
Built for SIP/8 kHz, <300 ms latency, multilingual, diarization, NER, summaries; one API for real-time + batch. - Option B: Built-in or self-hosted STT
May be fine on clean audio, but often less stable on noisy, multilingual 8 kHz calls; higher operational overhead for scaling and tuning. - Best for:
Teams where missed entities, wrong speakers, or latency spikes directly break agent assist, QA, or CRM workflows.
What do I need to implement Gladia for Twilio/SIP real-time transcription in production?
Short Answer: You need a Gladia API key, a small WebSocket bridge service, and access to Twilio/SIP media streaming; from there, you can roll out real-time transcription into your existing voice and CRM stack.
Expanded Explanation:
Implementation boils down to wiring, not heavy infra. You keep your existing Twilio numbers and SIP routing. You add a lightweight bridge service (Node, Python, Go—any stack that handles WebSockets) to connect Twilio/SIP streams to Gladia’s API. From there, it’s about how you consume the transcript: feed it into your agent UI, log it, trigger automation from entities or sentiment, and schedule batch post-processing when needed.
Because Gladia’s stack covers real-time and batch with the same engine, you can start with real-time assist and later add post-call QA, searchable archives, and CRM enrichment without reintegrating a different vendor.
What You Need:
- Gladia account & API key
To authenticate WebSocket and REST calls to the real-time and batch endpoints. - Media streaming access & bridge service
Twilio<Start><Stream>or SIP media tap, plus a WebSocket bridge server to relay audio and handle transcript events.
How does using Gladia strategically improve my Twilio/SIP call workflows and downstream data quality?
Short Answer: It reduces transcription errors on 8 kHz calls, stabilizes latency, and gives you reliable entities and speakers—so your notes, summaries, analytics, and CRM syncs don’t fall apart.
Expanded Explanation:
Most failures in voice products start with bad STT: wrong names, broken emails, mis-heard numbers, or the wrong speaker attached to the wrong statement. In telephony, this is amplified by 8 kHz bandwidth, noise, and crosstalk. Once the transcript is wrong, everything downstream—summaries, QA scores, automations, CRM updates—becomes untrustworthy.
By using Gladia as your central STT backbone for Twilio/SIP, you get consistent, benchmarked performance on conversational, noisy call audio. Real-time transcripts power live agent assist; diarized, timestamped transcripts feed QA and coaching; entities and numbers can populate CRM automatically; summaries make calls skimmable. Because the engine is the same for real-time and batch, your analytics don’t drift between live and post-call views.
Why It Matters:
- Higher information fidelity on 8 kHz calls
Fewer missed entities and misattributed speakers means your agent assist and automation logic can be trusted. - Stable, low-latency infrastructure
Predictable sub-300 ms streaming and telephony-aware design keep your Twilio/SIP experience responsive at scale.
Quick Recap
To use Gladia with Twilio/SIP calls at 8 kHz in real time, you stream call audio via WebSocket from Twilio or your SIP stack into a small bridge service, then forward that audio into Gladia’s real-time API. Gladia returns low-latency partial and final transcripts—with timestamps, diarization, and multilingual support—that you can plug into agent assist, live dashboards, and post-call workflows. The result: cleaner transcripts, fewer downstream failures, and one STT backbone for both real-time and batch telephony use cases.