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Course Outline
Introduction to Speech Synthesis and Voice Cloning <\/p>
- Overview of text-to-speech (TTS) and neural voice synthesis <\/li>
- Voice cloning vs speech generation: use cases and boundaries <\/li>
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Key models: Tacotron, WaveNet, FastSpeech, VITS
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Working with Commercial Platforms <\/p>
- Using ElevenLabs and Resemble AI <\/li>
- Voice creation, cloning, and editing <\/li>
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API access and text-to-speech workflows
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Building with Open-Source Tools <\/p>
- Installing and configuring Coqui TTS <\/li>
- Training custom voices and managing datasets <\/li>
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Generating speech with fine control (pitch, speed, emotion)
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Data Preparation and Voice Dataset Management <\/p>
- Collecting and cleaning voice samples <\/li>
- Segmenting, labeling, and aligning transcripts <\/li>
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Ethical sourcing and voice consent
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Application Integration <\/p>
- Embedding TTS in websites and applications <\/li>
- Creating IVR systems and interactive bots <\/li>
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Generating synthetic dialogue for video and games
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Evaluating Quality and Realism <\/p>
- MOS (Mean Opinion Score) and intelligibility tests <\/li>
- Controlling expressiveness and prosody <\/li>
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Comparing latency, fidelity, and realism
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Ethical, Legal, and Governance Considerations <\/p>
- Deepfake risks and responsible usage <\/li>
- Consent, attribution, and copyright implications <\/li>
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Regulations and organizational policies
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Summary and Next Steps <\/p>
Requirements
- Understanding of machine learning fundamentals <\/li>
- Familiarity with audio file formats and editing tools <\/li>
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Basic Python programming skills
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Audience<\/strong> <\/p>
- AI developers and engineers interested in speech synthesis <\/li>
- Content creators and media technologists exploring voice generation <\/li>
- R&D teams building personalized or dynamic audio systems <\/li> <\/ul>
14 Hours
