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Text-to-Speech & Audio AI Fundamentals

Introduces speech synthesis and audio generation pipelines—from text normalization to vocoders. Compare tools, evaluate naturalness and latency, and learn basic ethics for voice cloning and consent.

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Voice Synthesis and Audio Generation

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The Science of Creating Voices#

Voice synthesis is the process of artificially creating human-like speech. Modern AI systems can generate incredibly realistic voices that are almost indistinguishable from real humans.

Types of Voice Synthesis#

1. Concatenative Synthesis#

  • How it works: Combines pre-recorded speech segments
  • Pros: High quality for recorded content
  • Cons: Limited flexibility, large storage requirements

2. Parametric Synthesis#

  • How it works: Uses mathematical models to generate speech
  • Pros: Flexible, small file sizes
  • Cons: Can sound robotic

3. Neural Synthesis (AI-Powered)#

The Modern Approach
  • How it works: Uses deep learning to generate speech
  • Pros: Extremely natural, flexible, expressive
  • Cons: Requires powerful computers

Key Components of Voice Synthesis#

  • Pitch: How high or low the voice sounds
  • Tone: The emotional quality of the voice
  • Speed: How fast or slow the speech is
  • Accent: Regional pronunciation characteristics
  • Inflection: Changes in pitch that convey meaning

Common Technologies#

  • WaveNet: Google's neural audio generation
  • Tacotron: End-to-end speech synthesis
  • FastSpeech: Fast and controllable TTS
  • VALL-E: Voice cloning from short samples
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