Paper Info
Title
Development of the SRI/nightingale Arabic ASR system
Abstract
We describe the large vocabulary automatic speech recognition system developed for Modern Standard Arabic by the SRI/Nightingale team, and used for the 2007 GALE evaluation as part of the speech translation system. We show how system performance is affected by different development choices, ranging from text processing and lexicon to decoding system architecture design. Word error rate results are reported on broadcast news and conversational data from the GALE development and evaluation test sets. Index Terms: speech recognition, large vocabulary, Arabic
Year
Venue
Keywords
2008
INTERSPEECH
automatic speech recognition,system performance,system architecture,word error rate,speech recognition,indexing terms
Field
DocType
Citations 
Speech analytics,Computer science,Word error rate,Speech recognition,Lexicon,Modern Standard Arabic,Natural language processing,Artificial intelligence,Speech translation,Vocabulary,Speech technology,Text processing
Conference
14
PageRank 
References 
Authors
2.68
10
12
Name
Order
Citations
PageRank
Dimitra Vergyri137336.97
Arindam Mandal215816.44
Wen Wang332729.31
Andreas Stolcke46690712.46
Jing Zheng544243.00
Martin Graciarena628124.70
David Rybach718820.31
Christian Gollan826018.73
Ralf Schlüter91337136.18
Katrin Kirchhoff10102695.24
Arlo Faria11667.87
Nelson Morgan123048533.52