Paper Info
Title
Out of vocabulary detection in Indonesian speech recognition using word and syllable level decoding
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%.
Year
DOI
Venue
2011
10.1109/ICEEI.2011.6021790
Electrical Engineering and Informatics
Keywords
Field
DocType
decoding,error detection,speech coding,speech recognition,vocabulary,Indonesian speech recognition,POS tag method,alignment technique,language model,out of vocabulary word detection,part-of-speech tag method,syllable level decoding,word error recognition,word level decoding,acoustic model,alignment,false alarm,language model,out of vocabulary,speech recognition,syllable level decoding,tag,word level decoding
Speech coding,False alarm,Computer science,Speech recognition,Natural language processing,Syllable,Artificial intelligence,Decoding methods,Hidden Markov model,Vocabulary,Language model,Acoustic model
Conference
ISSN
ISBN
Citations 
2155-6822
978-1-4577-0753-7
0
PageRank 
References 
Authors
0.34
4
2
Name
Order
Citations
PageRank
Aswin Juari100.34
Purwarianti, A.2122.09