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  1. University of Computer Studies, Yangon
  2. Conferences

Building HMM-SGMM Continuous Automatic Speech Recognition on Myanmar Web News

http://hdl.handle.net/20.500.12678/0000004998
3e0d9b51-e165-49ca-9920-3ed3c11d5057
53a80d34-35d9-4d3f-a577-7dd810dec984
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proceeding_total-pages-446-453.pdf proceeding_total-pages-446-453.pdf (3734 Kb)
Publication type Article
Upload type Publication
Title
Building HMM-SGMM Continuous Automatic Speech Recognition on Myanmar Web News
en
Publication date 2017-02-16
Authors
Mon, Aye Nyein
Pa, Win Pa
Thu, Ye Kyaw
Description
Myanmar language is a tonal and analyticlanguage. It can be considered as an under-resourcedlanguage because of its linguistic resource availability.Therefore, speech data collection is a very challengingtask in building Myanmar automatic speechrecognition. Today a lot of speech data are freelyavailable on the Internet and we can collect it easily.Therefore, in this system, we take the advantages ofInternet and we use daily news from the Web inbuilding our speech corpus. In this paper, we willpresent about the task of data collection, the effect ofAutomatic Speech Recognition (ASR) performanceaccording to amount of training data, language modelsize and error analysis of the experimental result. Theexperiments will be developed using Hidden MarkovModel (HMM) with Gaussian Mixture Model (GMM)and Subspace Gaussian Mixture Model (SGMM). As aresult, using our developed 5 hours training data, thissystem achieves word error rate (WER) of 7.6% onclose test data and 31.9% on open test data withHMM-SGMM.
Keywords
Automatic Speech Recognition (ASR)
Keywords
speech corpus developing
Keywords
News Domain
Keywords
HMM-GMM
Keywords
HMM-SGMM
Keywords
Myanmar Language
Journal articles
Fifteenth International Conference on Computer Applications (ICCA 2017)
Conference papers
Books/reports/chapters
Thesis/dissertations
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