Text-to-Speech
Text-to-Speech is the speech-synthesis technology that converts written text into natural-sounding audio using neural networks. A modern pipeline tokenizes input, converts characters to phonemes, predicts mel-spectrograms with an acoustic model such as Tacotron 2, FastSpeech 2, or GPT-TTS, and then transforms the spectrogram into waveforms via a neural vocoder like WaveGlow or HiFi-GAN. Advanced systems support zero-shot voice cloning and emotion control through style tokens, letting apps render brand voices or multilingual output from a single model. Quality is measured by mean-opinion score (MOS) and real-time factor (RTF); low RTF enables streaming voice assistants, while high MOS ensures audiobooks remain engaging. Deployment options range from cloud APIs—Amazon Polly, Azure Neural TTS, ElevenLabs—to on-device models that meet GDPR by keeping audio local. Text-to-Speech powers screen readers, accessibility features, call-center bots, and Retrieval-Augmented Generation (RAG) chatbots that can “talk back,” turning static content into interactive voice experiences.
Want to learn how these AI concepts work in practice?
Understanding AI is one thing. Explore how we apply these AI principles to build scalable, agentic workflows that deliver real ROI and value for organizations.