DocumentCode :
3529109
Title :
A joint decoding algorithm for multiple-example-based addition of words to a pronunciation lexicon
Author :
Bansal, Dhananjay ; Nair, Nishanth ; Singh, Rita ; Raj, Bhiksha
Author_Institution :
Xtone Networks, Reston, VA
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
4293
Lastpage :
4296
Abstract :
We propose an algorithm that enables joint Viterbi decoding of multiple independent audio recordings of a word to derive its pronunciation. Experiments show that this method results in better pronunciation estimation and word recognition accuracy than that obtained either with a single example of the word or using conventional approaches to pronunciation estimation using multiple examples.
Keywords :
Viterbi decoding; speech coding; speech recognition; independent audio recordings; joint Viterbi decoding; joint decoding algorithm; pronunciation estimation; pronunciation lexicon; speech recognition systems; word recognition accuracy; words multiple-example-based addition; Audio recording; Automatic speech recognition; Bayesian methods; Decoding; Hidden Markov models; Lattices; Probability distribution; Speech recognition; US Department of Transportation; Viterbi algorithm; Joint decoding; Pronunciation estimation; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4960578
Filename :
4960578
Link To Document :
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