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ElevenLabs Audio Transcription via OpenRouter
ai
ElevenLabs Audio Transcription via OpenRouter is a paid API for AI agents from ElevenLabs at elevenlabs.mpp.tempo.xyz, paid per call via MPP, price unknown, status unknown (last checked 2026-10-29).
Transcribes a base64-encoded PCM WAV audio file (mono, 16-bit, 16 kHz, up to 10 minutes) into text using ElevenLabs speech-to-text models via OpenRouter.
Price / call—
Success—
StatusUnknown
How this service works
Transcribe base64 PCM WAV (mono, 16-bit, 16 kHz, up to 10 minutes; models and prices at GET /v1/audio/models)
Output
Returns the transcribed text content extracted from the audio, potentially including timestamped segments, detected language, and confidence scores depending on the selected model.
Example use cases
Interview recording to transcript
“I just recorded a 5-minute interview as a mono 16kHz WAV file — here's the base64-encoded audio. Can you transcribe everything that was said into text?”
Customer support call transcription
“I have a base64-encoded WAV recording of a customer support call (mono, 16-bit, 16 kHz, about 8 minutes). Transcribe it so I can review what was discussed.”
Meeting notes from voice memo
“Here's a base64 PCM WAV voice memo from today's team standup — it's mono, 16 kHz, just under 10 minutes. Please transcribe it so I can turn it into meeting notes.”
Technical details
Endpoint
POSThttps://elevenlabs.mpp.tempo.xyz/v1/audio/transcriptions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need speech-to-text transcription powered by ElevenLabs models via OpenRouter with one-shot micropayment support. Ideal when audio is already in the required PCM WAV format (mono, 16-bit, 16 kHz) and you want high-quality transcription without managing API keys or subscriptions.
Side effects
- Audio not in correct format (must be mono, 16-bit, 16 kHz PCM WAV)
- Audio exceeds 10-minute limit
- Invalid or malformed base64 encoding
- Unsupported or unavailable model ID
- Payment/authorization failure via x402 protocol
- Low audio quality leading to poor transcription accuracy
Tags
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