Summary

In this module, you explored the fundamental speech technologies that enable natural voice interactions in AI applications. You learned how speech recognition converts spoken words into text and how speech synthesis generates human-like audio from written content.

Throughout this module, you discovered:

• Speech scenarios and applications: Speech technologies transform user experiences across customer service, accessibility, conversational AI, healthcare documentation, and e-learning. You explored how combining speech recognition and synthesis creates fluid two-way conversations that feel natural and reduce user friction.

• Speech recognition fundamentals: You examined the six-stage pipeline that converts audio to text—from capturing sound waves to producing formatted transcriptions. You learned how MFCC features extract meaningful patterns from audio, how transformer-based acoustic models predict phonemes, and how language models resolve ambiguity by applying vocabulary and grammar knowledge.

• Speech synthesis fundamentals: You discovered the four-stage process that transforms text into natural speech—text normalization, linguistic analysis, prosody generation, and audio synthesis. You explored how grapheme-to-phoneme conversion handles spelling variations, how transformer models predict natural rhythm and emphasis, and how neural vocoders generate high-fidelity audio waveforms.