Voicecore.ai

Enterprise-Grade Features

✨

No Rate Limits

Self-hosted infrastructure means unlimited transcription capacity. Scale as much as you need.

🌍

Multi-Language

Hebrew, English, and 90+ languages supported. Automatic language detection included.

🔒

Privacy First

Your data stays on your servers. Complete control over sensitive audio and transcripts.

⚡

Lightning Fast

📊

99.9% Uptime

Enterprise-grade reliability with automatic failover and health monitoring.

💰

Predictable Pricing

No per-minute costs. Fixed monthly pricing regardless of usage volume.

Technical Specifications

Model

OpenAI Whisper Large-v3

Languages

90+ (Hebrew, English, Arabic, Spanish, etc.)

Supported Formats

MP3, WAV, M4A, FLAC, OGG, WebM

Max File Size

100 MB per file

API Type

REST/JSON

Authentication

None required (can be added)

API Documentation

Base URL: http://199.68.217.31:60582

Health Check: GET /health

Transcribe: POST /transcribe

Quick Start

cURL

Python

JavaScript

Response

# Health check
curl http://199.68.217.31:60582/health

# Transcribe audio file
curl -X POST http://199.68.217.31:60582/transcribe \
  -F "file=@audio.wav"

# Transcribe with specific language (optional)
curl -X POST http://199.68.217.31:60582/transcribe \
  -F "file=@audio.mp3" \
  -F "language=he"

import requests

# Transcribe audio file
with open('audio.wav', 'rb') as audio_file:
    response = requests.post(
        'http://199.68.217.31:60582/transcribe',
        files={'file': audio_file}
    )
    
    result = response.json()
    print(f"Text: {result['text']}")
    print(f"Language: {result['language']}")
    print(f"Duration: {result['duration']} seconds")

# Transcribe with language hint
response = requests.post(
    'http://199.68.217.31:60582/transcribe',
    files={'file': open('audio.mp3', 'rb')},
    data={'language': 'he'}  # Hebrew
)

// Using fetch API
const formData = new FormData();
formData.append('file', audioFile);

const response = await fetch('http://199.68.217.31:60582/transcribe', {
    method: 'POST',
    body: formData
});

const result = await response.json();
console.log('Transcription:', result.text);
console.log('Language:', result.language);

// Using axios
const axios = require('axios');
const FormData = require('form-data');
const fs = require('fs');

const form = new FormData();
form.append('file', fs.createReadStream('audio.wav'));

const response = await axios.post(
    'http://199.68.217.31:60582/transcribe',
    form,
    { headers: form.getHeaders() }
);

console.log(response.data);

// Successful response
{
    "text": "This is the transcribed text from your audio file.",
    "language": "en",
    "duration": 12.5
}

// Health check response
{
    "status": "healthy"
}

// Error response
{
    "error": "No file provided"
}

Supported Languages (90+)

en English • he Hebrew • ar Arabic • es Spanish • fr French • de German • it Italian • pt Portuguese • ru Russian • ja Japanese • ko Korean • zh Chinese • and 80+ more

Advanced Usage

# Batch processing example (Python)
import requests
import os

API_URL = "http://199.68.217.31:60582/transcribe"

def transcribe_file(file_path):
    with open(file_path, 'rb') as f:
        response = requests.post(API_URL, files={'file': f})
        return response.json()

# Process multiple files
audio_folder = "./audio_files"
for filename in os.listdir(audio_folder):
    if filename.endswith(('.wav', '.mp3', '.m4a')):
        file_path = os.path.join(audio_folder, filename)
        result = transcribe_file(file_path)
        print(f"{filename}: {result['text']}")