Course Production Workflow

  1. Course Outline: Structure modules and lectures
  2. Script Each Lecture: Write clear, instructional scripts
  3. Generate Audio: Kitten TTS produces all narration
  4. Sync with Slides: Match audio to presentation slides
  5. Publish: Upload to your platform of choice

Module-by-Module Script

from kittentts import KittenTTS
model = KittenTTS("KittenML/kitten-tts-mini-0.8")

modules = {
    "m1_intro": "Welcome to Python for Data Science. In this course you will master data analysis with Python.",
    "m1_lec1": "Lecture one: Setting up your Python environment. We will install Python and Jupyter Notebook.",
    "m1_lec2": "Lecture two: Variables and data types. Understanding integers, floats, strings, and booleans.",
    "m1_summary": "Module one summary: You have learned Python basics and environment setup.",
}

for filename, text in modules.items():
    model.generate_to_file(text, filename + ".wav", voice="Jasper", speed=0.95)
    print("Generated: " + filename)

print("Module one audio complete!")

Best Practices for Course Narration

  • Clear pronunciation: Use speed=0.95 for technical terms
  • Consistent voice: Same voice throughout the course
  • Section markers: Add "Module X, Lecture Y" for easy navigation
  • Summaries: Brief recap at end of each module