One of the major difficulties related to German LVCSR is the rich morphology nature of German, leading to high out-of-vocabulary (OOV) rates, and high language model (LM) perplexities. Normally, compound words make up an essential fraction of the German vocabulary. Most compound OOVs are composed of frequent in-vocabulary words. Here, we investigate the use of sub-lexical LMs based on different approaches for word decomposition, namely supervised and unsupervised decomposition, as well as decomposition derived from grapheme-to-phoneme (G2P) conversion. In the later approach, we augment a normal word model with a set of grapheme-phoneme pairs called graphones used to model the OOV words. A novel approach is proposed to select the representative graphone sequences for OOVs based on unsupervised decomposition and word-pronunciation alignment. We obtain relative reductions in word error rate (WER) from 4.2% to 6.5% with respect to a comparable full-words system.
M. Ali Basha ShaikAmr El-Desoky MousaRalf SchlüterHermann Ney
M. Ali Basha ShaikAmr El-Desoky MousaRalf SchlüterHermann Ney
Amr El-Desoky MousaM. Ali Basha ShaikRalf SchlüterHermann Ney
Amr El-Desoky MousaM. Ali Basha ShaikRalf SchlüterHermann Ney