Hermann NeyL. WellingS. OrtmannsK. BeulenFrank Wessel
We present an overview of the RWTH Aachen large vocabulary continuous speech recognizer. The recognizer is based on continuous density hidden Markov models and a time-synchronous left-to-right beam search strategy. Experimental results on the ARPA Wall Street Journal (WSJ) corpus verify the effects of several system components, namely linear discriminant analysis, vocal tract normalization, pronunciation lexicon and cross-word triphones, on the recognition performance.
Peter BeyerleinXavier AubertReinhold Haeb‐UmbachMatthew HarrisDietrich KlakowAndreas WendemuthSirko MolauHermann NeyMichael PitzAchim Sixtus
Achim SixtusSirko MolauStephan KanthakRalf SchlüterHermann Ney
Snehal Chandulal BajajKamal KantAmol BolePranaw Kumar
Hay Mar Soe NaingAye Mya HlaingWin Pa PaXinhui HuYe Kyaw ThuChiori HoriHisashi Kawai
Mahdi HamdaniPatrick DoetschMichał KozielskiAmr El-Desoky MousaHermann Ney