From the course: Fundamentals of Dynamic Programming

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What is a Hidden Markov Model?

What is a Hidden Markov Model? - Python Tutorial

From the course: Fundamentals of Dynamic Programming

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What is a Hidden Markov Model?

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- [Instructor] One real-world application of dynamic programming is the Hidden Markov Model. A concept used in machine learning applications. A Hidden Markov Model is a mathematical description of real-world phenomena. The description consists of hidden states that represent how the phenomena behaves, observations visible to you and probabilities tying the two together. The model can be used to answer questions about the phenomena. Let's see how this works out for a classic example, speech recognition. Here, we have our sound waves as our observations. The sound waves map to spoken syllables, Dy -na -mic. We want to infer the syllables using only the sound waves. To model this problem as a Hidden Markov Model, we start with our hidden states, the ground truth of our speech. These are the syllables. Each hidden state emits an observation. In this case, the sound waves. Each syllable produces a different sound wave.…

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