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Course Outline
Introduction to Speech Synthesis and Voice Cloning
- Overview of text-to-speech (TTS) and neural voice synthesis
- Voice cloning vs speech generation: use cases and boundaries
- Key models: Tacotron, WaveNet, FastSpeech, VITS
Working with Commercial Platforms
- Using ElevenLabs and Resemble AI
- Voice creation, cloning, and editing
- API access and text-to-speech workflows
Building with Open-Source Tools
- Installing and configuring Coqui TTS
- Training custom voices and managing datasets
- Generating speech with fine control (pitch, speed, emotion)
Data Preparation and Voice Dataset Management
- Collecting and cleaning voice samples
- Segmenting, labeling, and aligning transcripts
- Ethical sourcing and voice consent
Application Integration
- Embedding TTS in websites and applications
- Creating IVR systems and interactive bots
- Generating synthetic dialogue for video and games
Evaluating Quality and Realism
- MOS (Mean Opinion Score) and intelligibility tests
- Controlling expressiveness and prosody
- Comparing latency, fidelity, and realism
Ethical, Legal, and Governance Considerations
- Deepfake risks and responsible usage
- Consent, attribution, and copyright implications
- Regulations and organizational policies
Summary and Next Steps
Requirements
- Understanding of machine learning fundamentals
- Familiarity with audio file formats and editing tools
- Basic Python programming skills
Audience
- AI developers and engineers interested in speech synthesis
- Content creators and media technologists exploring voice generation
- R&D teams building personalized or dynamic audio systems
14 Hours
