NDLI: Out of vocabulary detection in Indonesian speech recognition using word and syllable level decoding

Content Provider	IEEE Xplore Digital Library
Author	Juari, A. Purwarianti, A.
Copyright Year	2011
Description	Author affiliation: Informatic Department, Institut Teknologi Bandung, Indonesia (Juari, A.; Purwarianti, A.)
Abstract	One of the problems in speech recognition is out of vocabulary words (OOV) because they can make some words error. Out of vocabulary words are the words that cannot be recognized by speech recognizer because there is no recognizing database. Alignment, language model, and POS Tag method is proposed in order to recognize word error because of OOV words. Word and syllable level decoding from speech recognizer is the input for this method. Alignment is applied to word and syllable level decoding to get some differences from word and syllable level decoding. After that, language model and tag are also applied to determine if the words are correct. Speech recognition accuracy is about 75% if OOV rate is 15,5%. The OOV detection process reaches about 87% precision and 75% recall. Experiments also show that by using OOV detection, speech recognizer accuracy is increased by 11%.
Starting Page	1
Ending Page	8
File Size	662683
Page Count	8
File Format	PDF
ISBN	9781457707537
ISSN	21556830
e-ISBN	9781457707520
DOI	10.1109/ICEEI.2011.6021790
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-17
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vocabulary syllable level decoding false alarm out of vocabulary Acoustics language model Decoding word level decoding Accuracy speech recognition Hidden Markov models Speech recognition acoustic model Speech tag alignment
Content Type	Text
Resource Type	Article

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