Lilly Tech Systems
Text-to-Speech
Master modern speech synthesis technology — from understanding how TTS works under the hood (WaveNet, Tacotron) to using APIs from ElevenLabs, Google, Azure, and Amazon, customizing voices with SSML, and building multi-language applications.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is text-to-speech? History, use cases, and the evolution from robotic voices to human-quality neural speech synthesis.
2. How TTS Works
The science behind speech synthesis: text analysis, phoneme conversion, WaveNet, Tacotron, VITS, and neural vocoder architectures.
3. TTS APIs
Hands-on with ElevenLabs, Google Cloud TTS, Azure Speech, and Amazon Polly. API setup, code examples, pricing, and comparison.
4. Neural Voices
Understanding neural voice technology: voice cloning, custom voices, emotional expression, and the latest advances in voice quality.
5. SSML
Speech Synthesis Markup Language for fine-grained control: pauses, emphasis, pronunciation, prosody, and multi-language speech.
6. Best Practices
Production deployment, performance optimization, accessibility, ethical considerations, and building great TTS user experiences.
What You'll Learn
By the end of this course, you'll be able to:
Understand TTS
Know how modern neural TTS systems convert text to natural-sounding speech using deep learning architectures like WaveNet and Tacotron.
Use TTS APIs
Integrate text-to-speech into your applications using APIs from ElevenLabs, Google Cloud, Azure, and Amazon with practical code examples.
Customize Voices
Control speech output with SSML markup, adjust prosody, add pauses, change pronunciation, and work with multi-language content.
Deploy in Production
Build production-ready TTS applications with proper caching, streaming, fallback strategies, and accessibility best practices.