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Course Outline
Introduction to Speech Synthesis and Voice Cloning
- Overview of Text-to-Speech (TTS) and neural voice synthesis.
- Distinctions between voice cloning and speech generation: applications and limits.
- Key models: Tacotron, WaveNet, FastSpeech, and VITS.
Working with Commercial Platforms
- Utilizing ElevenLabs and Resemble AI.
- Creating, cloning, and editing voices.
- 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-grained control (pitch, speed, emotion).
Data Preparation and Voice Dataset Management
- Collecting and cleaning voice samples.
- Segmenting, labeling, and aligning transcripts.
- Ethical sourcing and obtaining voice consent.
Application Integration
- Embedding TTS into websites and applications.
- Developing IVR systems and interactive bots.
- Generating synthetic dialogue for video and gaming content.
Evaluating Quality and Realism
- Conducting 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 practices.
- Consent, attribution, and copyright implications.
- Relevant regulations and organizational policies.
Summary and Next Steps
Requirements
- Foundational knowledge of machine learning principles.
- Familiarity with audio file formats and editing tools.
- Basic proficiency in Python programming.
Audience
- AI developers and engineers focusing on speech synthesis.
- Content creators and media technologists investigating voice generation technologies.
- R&D teams developing personalized or dynamic audio systems.
14 Hours
