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Course Outline
Fundamentals of Speech Synthesis and Voice Cloning
- Introduction to text-to-speech (TTS) and neural voice synthesis
- Distinguishing voice cloning from speech generation: applicable scenarios and limitations
- Key architectures: Tacotron, WaveNet, FastSpeech, VITS
Leveraging Commercial Platforms
- Working with ElevenLabs and Resemble AI
- Creating, cloning, and refining voices
- Utilizing API access and text-to-speech workflows
Developing with Open-Source Solutions
- Setting up and configuring Coqui TTS
- Training custom voices and managing datasets
- Producing speech with precise control over pitch, speed, and emotion
Data Preparation and Voice Dataset Curation
- Gathering and refining voice samples
- Segmenting, labeling, and aligning transcripts
- Ensuring ethical sourcing and obtaining voice consent
Integration into Applications
- Embedding TTS capabilities into websites and software applications
- Building IVR systems and interactive bots
- Generating synthetic dialogue for video content and gaming
Assessing Quality and Realism
- Conducting MOS (Mean Opinion Score) and intelligibility evaluations
- Managing expressiveness and prosody
- Comparing latency, fidelity, and realistic quality
Ethical, Legal, and Governance Frameworks
- Addressing deepfake risks and promoting responsible usage
- Navigating consent, attribution, and copyright issues
- Understanding regulatory requirements and organizational policies
Conclusions and Future Directions
Requirements
- Solid grasp of machine learning fundamentals
- Proficiency with audio file formats and editing software
- Foundational Python programming capabilities
Target Audience
- AI developers and engineers focused on speech synthesis
- Content creators and media specialists interested in voice generation
- R&D teams developing personalized or dynamic audio systems
14 Hours
