NDLI: Pronunciation Recognition and Assessment for Mandarin Chinese

Content Provider	IEEE Xplore Digital Library
Author	Zhong, Cencen Miao, Zhenjiang
Copyright Year	2008
Abstract	This paper establishes a speaker-independent pronunciation recognition and assessment system with 673 words for mandarin Chinese under the background of a Chinese learning system framework. The recognition part is based on HTK using HMM (Hidden Markov Models) and improved in the aspect of acoustic model. Making use of the recognition results and the log-likelihood obtained from the Viterbi coding, the machine scoring is performed to evaluate the quality of pronunciation. Finally the assessment approach based on log probability is combined with the pronunciation recognition system established. The machine score and its correlation with expert score are discussed and the experimental result shows that the scores are close to people's subjective scoring.
Starting Page	352
Ending Page	356
File Size	345915
Page Count	5
File Format	PDF
ISBN	9780769531199
DOI	10.1109/CISP.2008.454
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Log-likelihood Image recognition Natural languages HMM Pattern recognition Learning systems Information science Viterbi algorithm Hidden Markov models Speech recognition Signal processing Pronunciation Assessment Pronunciation Recognition HTK
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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