Speaker Map

Batch audio and video transcription with speaker diarization. Process hundreds of files with GPU-accelerated AI models.

Why Speaker Map?

GPU-Accelerated

Leverage NVIDIA GPUs for fast transcription. Process hours of audio in minutes with CUDA-optimized Whisper models.

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Speaker Diarization

Automatically identify and label different speakers. Know who said what with speaker-aware transcription.

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Batch Processing

Queue and process hundreds of audio and video files. Supports MP3, WAV, MP4, MKV, and more.

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On-Premise

Run on your own hardware. Your data never leaves your network. Full control over your transcription pipeline.

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Client-Server

Backend server processes transcriptions. Desktop client for easy file management. Multiple users, one server.

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Multiple Formats

Export transcripts as TXT, SRT, VTT, or JSON. Timestamps, speaker labels, and confidence scores included.

Pricing

One-time purchase. No subscriptions for the software.

Backend Server

$400 CAD

  • GPU-accelerated transcription
  • All Whisper model sizes
  • Speaker diarization
  • Unlimited file processing
  • REST API access
  • 1 server license
Purchase

Frontend Client

$100 CAD / seat

  • Desktop application
  • Drag-and-drop file management
  • Batch queue management
  • Real-time progress tracking
  • Export to TXT, SRT, VTT, JSON
  • 1 seat license
Purchase
BEST VALUE

Bundle

$500 CAD

  • Backend Server license
  • Frontend Client license
  • All features included
  • Save $100 over separate
  • Priority setup support
  • 1 server + 1 seat
Purchase

System Requirements

Backend Server

  • OS: Windows 10/11, Ubuntu 22.04+
  • GPU: NVIDIA GPU with 8GB+ VRAM (RTX 3060 or better)
  • RAM: 16GB minimum
  • Storage: 10GB for models + space for audio files
  • CUDA: 11.8 or 12.x
  • Python: 3.10+

Frontend Client

  • OS: Windows 10/11
  • RAM: 4GB minimum
  • Storage: 200MB for application
  • Network: LAN access to backend server

Ready to get started?

Create an account, purchase a license, and start transcribing in minutes.

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