Pre-Recorded Audio
Upload pre-recorded audio files for high-quality batch transcription. Perfect for podcasts, meetings, interviews, and media content.
Batch Endpoints
POST
/api/v1/stt/transcribeUniversal endpoint - automatically routes to the best engine based on selected model.
POST
/api/v1/stt/cipher/transcribeCipher engine endpoint - use for cipher-fast and cipher-max models.
POST
/api/v1/stt/lucid/transcribeLucid engine endpoint - use for lucid-mono, lucid-multi, lucid-agent, lucid-lite models.
Cipher Models
Optimized for batch transcription with excellent accuracy and speed.
| Model | Description | Credits/sec | Best For |
|---|---|---|---|
cipher-fast | Ultra-fast transcription | 2 | Quick turnaround, general content |
cipher-max | Maximum accuracy | 2 | Complex audio, accents, technical content |
Cipher Features
- Language Detection: Automatic detection or specify from 90+ languages
- Word Timestamps: Granular word-level timing for precise alignment
- Context Prompt: Guide the model with domain-specific terms and phrases
- Multiple Formats: JSON, text, verbose_json, SRT, VTT output formats
Lucid Models (Batch)
Enterprise-grade batch transcription with advanced features.
| Model | Description | Credits/sec | Best For |
|---|---|---|---|
lucid-mono | High-accuracy single language | 3 | Single-language content |
lucid-multi | Multilingual support | 3 | Mixed-language content |
lucid-agent | Conversational optimized | 3 | Phone calls, support recordings |
lucid-lite | Cost-effective option | 3 | High volume processing |
Lucid Features
- Speaker Diarization: Identify and label different speakers in conversations
- Keywords Boost: Improve recognition accuracy for specific words
- Smart Formatting: Auto-format dates, numbers, and currency
- Punctuation: Automatic punctuation insertion
Basic Request Example
import requests
url = "https://yourvoic.com/api/v1/stt/transcribe"
headers = {"X-API-Key": "your_api_key"}
with open("audio.mp3", "rb") as f:
response = requests.post(url, headers=headers,
files={"file": f},
data={"model": "cipher-fast"})
result = response.json()
print(result["text"])