DocumentCode :
3240067
Title :
Acoustic training system for speaker independent continuous Arabic speech recognition system
Author :
Nofal, Maged ; Abdel-Raheem, Esam ; El Henawy, Hadia ; Kader, N.A.
Author_Institution :
Ain Shams Univ., Cairo, Egypt
fYear :
2004
fDate :
18-21 Dec. 2004
Firstpage :
200
Lastpage :
203
Abstract :
The paper presents an acoustic training system for building acoustic models for a medium vocabulary speaker independent continuous speech recognition system. A speech database is constructed to train the acoustic models. The acoustic models are constructed, and trained. A test set database is constructed to test the accuracy of the acoustic models. Also 4 language models of two main types: bigram and context free grammar, were built and used in tests. Our results show 5.26% and 2.72% word error rates for 1340 and 306 words bigram based language models, respectively. Our results show also 0.19% and 0.99% word error rates for 1340 and 306 words context free grammar based language models, respectively.
Keywords :
Gaussian processes; acoustic signal processing; context-free grammars; database languages; hidden Markov models; natural languages; speaker recognition; vocabulary; acoustic model; acoustic training system; bigram; context free grammar; continuous Arabic speech recognition system; language model; signal construction; speech database; vocabulary speaker independent system; word error rate; Acoustic testing; Automatic speech recognition; Context modeling; Databases; Error analysis; Hidden Markov models; Loudspeakers; Natural languages; Speech recognition; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology, 2004. Proceedings of the Fourth IEEE International Symposium on
Print_ISBN :
0-7803-8689-2
Type :
conf
DOI :
10.1109/ISSPIT.2004.1433721
Filename :
1433721
Link To Document :
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