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Course Outline
Introduction to Voice Cloning and Speech Synthesis
- Overview of text-to-speech (TTS) and neural voice synthesis.
- Distinguishing between voice cloning and speech generation: use cases and limits.
- Key architectures: Tacotron, WaveNet, FastSpeech, and VITS.
Utilizing Commercial Platforms
- Working with ElevenLabs and Resemble AI.
- Creating, cloning, and refining voices.
- Managing API access and TTS workflows.
Developing with Open-Source Tools
- Setting up and configuring Coqui TTS.
- Training custom voices and handling datasets.
- Generating speech with precise control over pitch, speed, and emotion.
Data Preparation and Voice Dataset Handling
- Gathering and cleaning voice samples.
- Segmenting, labeling, and aligning transcripts.
- Ensuring ethical sourcing and obtaining voice consent.
Integration into Applications
- Embedding TTS capabilities into websites and apps.
- Building IVR systems and interactive bots.
- Producing synthetic dialogue for video and gaming.
Assessing Quality and Realism
- Conducting MOS (Mean Opinion Score) and intelligibility evaluations.
- Managing expressiveness and prosody.
- Comparing latency, fidelity, and realism.
Ethical, Legal, and Governance Frameworks
- Addressing deepfake risks and ensuring responsible usage.
- Navigating consent, attribution, and copyright issues.
- Aligning with regulations and organizational policies.
Conclusion and Future Directions
Requirements
- Solid grasp of machine learning fundamentals.
- Experience with audio file formats and editing software.
- Foundational Python programming knowledge.
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.
14 Hours
