A Hidden Markov Model (HMM) is a statistical model used in speech recognition and natural language processing. It works by predicting sequences of events—like sounds or words—based on probabilities. In voice AI, HMMs help decode spoken language by mapping sounds to likely word sequences. While newer deep learning models are more common now, HMMs laid the foundation for many early voice technologies and are still used in specific applications.
