AI-Powered Automated Transcription and Metadata Generation
Overview
Audimus.Server is an AI-powered platform for automated transcription and metadata generation of pre-recorded audio and video content across media, enterprise, and institutional workflows.
The system combines proprietary Automatic Speech Recognition (ASR), advanced audio processing, Natural Language Processing (NLP), and computer vision technologies to generate accurate transcriptions enriched with semantic metadata, including speaker identification, language detection, and topic classification.
Supporting 50+ languages and simultaneous translation, Audimus.Server enables organizations to efficiently process, index, and retrieve large volumes of media content.
Designed for flexible post-production environments, the platform integrates seamlessly with Media Asset Management (MAM) systems and existing workflows via web interface, watch folders, or REST APIs.
Deployed on-premises, Audimus.Server ensures secure, high-performance processing while maintaining full control over sensitive media assets.
What's New in Version 7.2
Enhanced processing performance with faster-than-real-time transcription (up to 2× playback speed)
Improved metadata generation with advanced topic detection and semantic indexing
Expanded computer vision capabilities for facial recognition and OCR-based content extraction
Enhanced REST API for deeper workflow integration
Improved web interface for task management, editing, and collaboration
Key Benefits
Automated transcription at scale
Process large volumes of audio and video files with minimal manual intervention
Rich metadata generation
Automatically generate searchable metadata including speakers and topics
Faster-than-real-time processing
Transcribe up to twice the duration of content within the same processing window
Workflow automation
Integrate seamlessly with existing systems using watch folders and APIs
Content discoverability
Enable full-text search across spoken content without manual tagging
Key Features
Applications
Media asset management and archive indexing
High-volume transcription
Content repurposing and subtitling
Corporate media workflows
Legal, compliance, and documentation workflows
Education and research transcription
Deployment
The platform operates as a scalable batch-processing system, supporting fast processing times depending on hardware configuration
Flexible deployment options allow integration into existing production, archive, and content management environments
Technical Specifications
Speech Processing
Automatic transcription engine
Language Processing
NLP formatting and text processing
Speaker Identification
Speaker detection and diarization
Content Identification
Computer Vision (Face ID, OCR)
Metadata Engine
Topic detection, indexing
Management Interface
Web-based task dashboard
Operating Systems
Windows 10 / 11, Windows Server 2016–2022
CPU
Intel Core i7 or equivalent (6+ cores)
CPU Speed
3.5 GHz recommended
Memory
Minimum 32 GB RAM
Processing
CPU-based architecture
GPU
Not required
Processing speed hardware-dependent
Scalable distributed processing
Input Interfaces
TYPE
SOURCES
All standard non-proprietary audio and video formats
Automated file ingestion via monitored directories
Manual upload and task configuration
REST-based integration with external systems
Output Formats
TYPE
EXAMPLES
DOCX, TXT, XML
SRT, WebVTT, TTML, STL, SCC
JSON, XML, XMP
MP4 (with embedded subtitles)
File export
Downloadable media
MAM integration
Direct ingestion
API delivery
Automated delivery via REST endpoints
Integrations
Media Asset Management (MAM) systems
Content archive and indexing platforms
Enterprise workflow systems
Custom integrations via REST API
Language Support
Languages
50+ supported
Translation
Simultaneous translation
Vocabulary
Custom vocabulary adaptation
Performance
Processing speed
than real-time
Timecoding
timestamps with confidence scoring
Security
Authentication
Token-based authentication
SSO
Active Directory, ADFS, SAML support
Encryption
TLS 1.3 secure communication
Access Control
Role-based user management
Licensing
License Type
Task-based licensing
License Allocation
1 license per transcription task
Scalability
Supports parallel processing with additional licenses
From speech to value
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