DocumentCode
3240899
Title
Hardware oriented architectures for continuous-speech speaker-independent ASR systems
Author
Cardarilli, Gian Carlo ; Malatesta, Alessandro ; Re, Marco ; Arnone, Luigi ; Bocchio, Sara
Author_Institution
Dept. of Electron. Eng., Tor Vergata Univ., Rome, Italy
fYear
2004
fDate
18-21 Dec. 2004
Firstpage
346
Lastpage
352
Abstract
In this paper we focus on the design and development of high performance speech recognition systems. The main problem with state-of-the-art speech recognition systems software is the uneven balance of accuracy and speed: systems with high level of accuracy tend to be extremely slow while fast systems have a degree of accuracy not suitable for most general purpose applications. We propose to speed up the system by performing the most computationally demanding task with dedicated hardware. We firstly analyse some commonly used ASR algorithms in order to choose the most suitable one. Then we develop a parallel hardware architecture that implements the selected algorithm. Finally we show how we described the proposed architectural model using the SystemC extension to the C++ programming language. Simulation results are given, along with reference tests made with the HTK´s speech recogniser for comparison purposes.
Keywords
C++ language; hidden Markov models; parallel architectures; speech recognition; ASR algorithm; C++ programming language; continuous-speech speaker-independent automatic speech recognition system; hardware oriented architecture; hidden Markov model; parallel hardware architecture; Automatic speech recognition; Computer architecture; Computer languages; Costs; Face recognition; Fats; Hardware; Hidden Markov models; Speech recognition; Vocabulary;
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.2004.1433791
Filename
1433791
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