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Course Outline

Foundations of Speech Synthesis and Voice Cloning

  • Introduction to Text-to-Speech (TTS) and neural voice synthesis techniques
  • Distinguishing between voice cloning and speech generation: applications and limits
  • Examination of key models: Tacotron, WaveNet, FastSpeech, and VITS

Leveraging Commercial Platforms

  • Working with ElevenLabs and Resemble AI
  • Creating, cloning, and refining voices
  • Navigating API access and text-to-speech workflows

Developing with Open-Source Solutions

  • Setup and configuration of Coqui TTS
  • Training bespoke voices and handling datasets
  • Producing speech with precise control over pitch, pace, and emotion

Data Handling and Voice Dataset Administration

  • Gathering and purifying voice samples
  • Segmenting audio, labeling data, and aligning transcripts
  • Ensuring ethical sourcing and obtaining voice consent

Integration into Applications

  • Embedding TTS functionality into websites and apps
  • Designing IVR systems and interactive chatbots
  • Generating synthetic dialogue for video games and visual media

Assessing Quality and Authenticity

  • Conducting MOS (Mean Opinion Score) and intelligibility assessments
  • Managing expressiveness and prosody
  • Comparing performance in terms of latency, fidelity, and realism

Ethical, Legal, and Governance Frameworks

  • Mitigating deepfake risks and promoting responsible usage
  • Addressing consent, attribution, and copyright concerns
  • Aligning with regulations and internal organizational policies

Recap and Future Directions

Requirements

  • Solid grasp of machine learning basics
  • Proficiency with audio file formats and editing software
  • Foundational Python programming knowledge

Target Audience

  • AI developers and engineers focused on speech synthesis technologies
  • Content creators and media technologists investigating voice generation tools
  • R&D teams developing personalized or dynamic audio systems
 14 Hours

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