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Schița de curs
Fundamentals of Audio and Noise
- Key concepts: waveform, frequency, amplitude, and dynamic range
- Types of noise: environmental, equipment, digital artifacts
- Traditional vs AI-driven noise reduction approaches
Overview of AI-Based Audio Enhancement Tools
- How AI models process and clean audio
- Tool comparison: Krisp, Adobe Enhance, RNNoise, NVIDIA RTX Voice
- Deployment options: local, cloud, and real-time integration
Using Krisp for Real-Time Conferencing
- Installation and setup on Windows/macOS
- Integration with Zoom, Teams, and Skype
- Live audio tests and troubleshooting common issues
Enhancing Recordings with Adobe Enhance
- Uploading and cleaning podcast-style recordings
- Limitations, latency, and quality control
- Using in combination with Adobe Audition or Premiere
Deploying RNNoise in Custom Pipelines
- Overview of RNNoise open-source library
- Compiling and using RNNoise with FFmpeg
- Custom integrations in surveillance or VoIP systems
Evaluating Quality and Performance
- Metrics: signal-to-noise ratio, latency, CPU/GPU impact
- Testing across use cases: meetings, recordings, field audio
- Human perception vs objective scoring tools
Case Studies and Workflow Integration
- Enterprise conferencing setup for legal and finance sectors
- Noise reduction in media production pipelines
- Audio cleaning for evidence and surveillance review
Summary and Next Steps
Cerințe
- An understanding of basic digital audio concepts
- Familiarity with using audio editing or communication tools
Audience
- Audio engineers
- IT support teams
- Media production units
14 ore