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A First Study on Hidden Markov Models and one Application in Speech Recognition
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Speech is intuitive, fast and easy to generate, but it is hard to index and easy to forget. What is more, listening to speech is slow. Text is easier to store, process and consume, both for computers and for humans, but writing text is slow and requires some intention. In this thesis, we study speech recognition which allows converting speech into text, making it easier both to create and to use information. Our tool of study is Hidden Markov Models which is one of the most important machine learning models in speech and language processing.

The aim of this thesis is to do a rst study in Hidden Markov Models and understand their importance, particularly in speech recognition. We will go through three fundamental problems that come up naturally with Hidden Markov Models: to compute a likelihood of an observation sequence, to nd an optimal state sequence given an observation sequence and the model, and to adjust the model parameters. A solution to each problem will be given together with an example and the corresponding simulations using MatLab. The main importance lies in the last example, in which a rst approach to speech recognition will be done.

Place, publisher, year, edition, pages
2016. , 51 p.
Series
LiTH-MAT-INT-B, 2016:01
Keyword [en]
Markov chain, Hidden Markov model (HMM), Speech recognition, MatLab simulation.
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-123912ISRN: LiTH-MAT-INT-B--2016/01--SEOAI: oai:DiVA.org:liu-123912DiVA: diva2:893683
Subject / course
Mathematics
Supervisors
Examiners
Available from: 2016-01-13 Created: 2016-01-13 Last updated: 2016-01-28Bibliographically approved

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First Study on Hidden Markov Models and one Application in Speech Recognition(392 kB)945 downloads
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf