Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä

Tämä tutkielma kuvaa erään tavan mallintaa kirjain-äännevastaavuuksien oppimista. Malli on luotu Ekapeliä varten käyttäen apuna pelistä kerättyä dataa. Mallin toteutuksessa käytettiin bayesilaisen tilastotieteen menetelmiä. Tavoitteena oli käyttää mallia uuden adaptaation luomiseen. Malli ei kuiten...

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Main Author: Venäläinen, Irene
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Format: Master's thesis
Language:fin
Published: 2019
Subjects:
Online Access: https://jyx.jyu.fi/handle/123456789/66431
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author Venäläinen, Irene
author2 Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä
author_facet Venäläinen, Irene Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä Venäläinen, Irene Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä
author_sort Venäläinen, Irene
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description Tämä tutkielma kuvaa erään tavan mallintaa kirjain-äännevastaavuuksien oppimista. Malli on luotu Ekapeliä varten käyttäen apuna pelistä kerättyä dataa. Mallin toteutuksessa käytettiin bayesilaisen tilastotieteen menetelmiä. Tavoitteena oli käyttää mallia uuden adaptaation luomiseen. Malli ei kuitenkaan sopinut suoraan pelin adaptaatiossa käytettäväksi laskennallisista ongelmista johtuen. Mallin avulla haluttiin myös visualisoida pelaajan osaamista ja kuvaajien avulla voidaankin helposti näyttää kokonaiskuva kirjainten osaamisesta. This thesis describes a bayesian model for learning letter-sound correspondences. The model was created for Ekapeli using data from the game. The model was created using bayesian methods. Purpose of the model was to create a new adaptation for Ekapeli. Because of high computational time, the model doesn't suite for an adaptation without simplifications. Another goal for the model was to help visualize the player's learning. The model suited well for visualizing the player's knowledge of the letter-sound correspondences.
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spellingShingle Venäläinen, Irene Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä bayesilainen tilastotiede Ekapeli Markovin ketju Monte Carlo Tietotekniikka Mathematical Information Technology 602 oppimispelit Markovin ketjut pelit
title Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
title_full Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
title_fullStr Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
title_full_unstemmed Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
title_short Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
title_sort kirjain äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
title_txtP Kirjain-äännevastaavuuden oppimisen mallinnus bayesilaisella menetelmällä
topic bayesilainen tilastotiede Ekapeli Markovin ketju Monte Carlo Tietotekniikka Mathematical Information Technology 602 oppimispelit Markovin ketjut pelit
topic_facet 602 Ekapeli Markovin ketju Monte Carlo Markovin ketjut Mathematical Information Technology Tietotekniikka bayesilainen tilastotiede oppimispelit pelit
url https://jyx.jyu.fi/handle/123456789/66431 http://www.urn.fi/URN:NBN:fi:jyu-201911204944
work_keys_str_mv AT venäläinenirene kirjainäännevastaavuudenoppimisenmallinnusbayesilaisellamenetelmällä