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Duration 14 hours (2 days)
Course Outline
Foundations of Speech Synthesis and Voice Cloning
- Introduction to Text-to-Speech (TTS) and neural voice synthesis
- Distinguishing voice cloning from speech generation: applications and limitations
- Core models including Tacotron, WaveNet, FastSpeech, and VITS
Leveraging Commercial Platforms
- Utilizing ElevenLabs and Resemble AI
- Processes for voice creation, cloning, and refinement
- Managing API access and TTS workflows
Developing with Open-Source Tools
- Setup and configuration of Coqui TTS
- Training custom voices and overseeing dataset management
- Producing speech with precise control over pitch, speed, and emotion
Data Preparation and Voice Dataset Management
- Gathering and refining voice samples
- Segmenting, labeling, and aligning transcripts
- Ensuring ethical sourcing and obtaining voice consent
Application Integration
- Incorporating TTS into websites and digital applications
- Building IVR systems and interactive chatbots
- Generating synthetic dialogue for video games and multimedia
Assessing Quality and Realism
- Applying MOS (Mean Opinion Score) and intelligibility benchmarks
- Adjusting expressiveness and prosody
- Evaluating latency, audio fidelity, and realism
Ethical, Legal, and Governance Frameworks
- Navigating deepfake risks and ensuring responsible usage
- Addressing consent, attribution, and copyright considerations
- Understanding regulatory compliance and organizational policies
Recap and Future Directions
Requirements
- Solid grasp of core machine learning concepts
- Proficiency with audio file formats and editing software
- Foundational skills in Python programming
Target Audience
- AI developers and engineers specializing in speech synthesis
- Content creators and media technologists exploring voice generation
- R&D teams developing personalized or dynamic audio systems