Building Speech-Enabled Generative AI Applications

Voice adds a natural, human layer to how we interact with technology. Building applications that can listen, understand, and speak back is a highly sought-after development skill. This text-based course guides you through the foundational concepts and practical steps to build speech-capable generative AI systems. You will transition from understanding how digital audio works to creating an end-to-end voice pipeline that transcribes user speech, processes it with a language model, and synthesizes a natural voice response. In this course, you will learn to: 1. Understand the core concepts of digital audio processing, speech transcription, and voice synthesis. 2. Transcribe spoken audio into clean text using modern speech-to-text APIs. 3. Connect transcription outputs to generative language models for intelligent text processing. 4. Synthesize text responses back into natural-sounding speech with modern text-to-speech engines. 5. Handle latency, streaming audio, and real-time interaction patterns in voice applications. 6. Apply basic prompt engineering to optimize language model responses for spoken conversations. Starting with essential terminology and audio fundamentals, the text-based lessons guide you step-by-step through configuring API connections, managing text and audio pipelines, and assembling a complete conversational loop in Python. This program is designed for software developers, product builders, and tech enthusiasts who are new to audio AI. A basic understanding of Python is helpful, but no prior experience with speech processing or machine learning is required. Start reading today and build your first voice-capable AI application.