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Hands-On Markov Models with Python

You're reading from   Hands-On Markov Models with Python Implement probabilistic models for learning complex data sequences using the Python ecosystem

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781788625449
Length 178 pages
Edition 1st Edition
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Authors (2):
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Ankur Ankan Ankur Ankan
Author Profile Icon Ankur Ankan
Ankur Ankan
Abinash Panda Abinash Panda
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Abinash Panda
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Summary

In this chapter, we looked into two of the major applications of HMMs: POS tagging and speech recognition. We coded the POS tagger using a most-frequent tag algorithm and used the pomegranate package to build one based on HMM. We compared the performance using both these methods and saw that an HMM-based approach outperforms the most-frequent tag method. Then, we used the SpeechRecognition package to transcribe audio to text using Google's Web Speech API. We looked into using the package with both audio files and live audio from a microphone.

In the next chapter, we will explore more applications of HMMs, specifically in the field of image recognition.

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