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Developing acoustic models for automatic speech recognition in swedish
KTH, Superseded Departments, Speech, Music and Hearing.ORCID iD: 0000-0002-3323-5311
1999 (English)In: The European Student Journal of Language and Speech, Vol. 1Article in journal (Refereed) Published
Abstract [en]

This thesis is concerned with automatic continuous speech recognition using trainable systems. The aim of this work is to build acoustic models for spoken Swedish. This is done employing hidden Markov models and using the SpeechDat database to train their parameters. Acoustic modeling has been worked out at a phonetic level, allowing general speech recognition applications, even though a simplified task (digits and natural number recognition) has been considered for model evaluation. Different kinds of phone models have been tested, including context independent models and two variations of context dependent models. Furthermore many experiments have been done with bigram language models to tune some of the system parameters. System performance over various speaker subsets with different sex, age and dialect has also been examined. Results are compared to previous similar studies showing a remarkable improvement.

Place, publisher, year, edition, pages
1999. Vol. 1
Keyword [en]
fonética, modelos, suecia
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-53564OAI: diva2:470353
QC 20120103Available from: 2011-12-28 Created: 2011-12-28 Last updated: 2012-01-03Bibliographically approved

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Salvi, Giampiero
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