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Duration 14 hours (2 days)
Course Outline
Introduction to Speech Synthesis and Voice Cloning
- Overview of text-to-speech (TTS) and neural voice synthesis technologies
- Distinguishing voice cloning from speech generation: use cases and operational boundaries
- Analysis of key models including Tacotron, WaveNet, FastSpeech, and VITS
Utilizing Commercial Platforms
- Practical application of ElevenLabs and Resemble AI
- Processes for voice creation, cloning, and audio editing
- Navigating API access and text-to-speech workflows
Developing with Open-Source Tools
- Installation and configuration of Coqui TTS
- Training custom voices and overseeing dataset management
- Generating speech with precise control over pitch, speed, and emotion
Data Preparation and Voice Dataset Management
- Methods for collecting and refining voice samples
- Techniques for segmenting, labeling, and aligning transcripts
- Ensuring ethical sourcing and obtaining proper voice consent
Application Integration
- Embedding TTS capabilities into websites and software applications
- Building IVR systems and interactive chatbots
- Producing synthetic dialogue for video content and gaming environments
Quality and Realism Evaluation
- Conducting MOS (Mean Opinion Score) and intelligibility assessments
- Managing expressiveness and prosody in output
- Benchmarking latency, audio fidelity, and perceived realism
Ethical, Legal, and Governance Frameworks
- Mitigating deepfake risks through responsible usage
- Navigating consent, attribution, and copyright considerations
- Compliance with relevant regulations and internal organizational policies
Recap and Future Directions
Requirements
- A solid grasp of fundamental machine learning concepts
- Familiarity with audio file formats and editing software
- Proficiency in basic Python programming
Target Audience
- AI developers and engineers with an interest in speech synthesis
- Content creators and media technologists exploring voice generation
- R&D teams developing personalized or dynamic audio systems