  Transcription of broadcast news is an interesting and challenging application
for large-vocabulary continuous speech recognition (LVCSR). We present in
detail the structure of a manually segmented and annotated corpus including
over 160 hours of German broadcast news, and propose it as an evaluation
framework of LVCSR systems. We show our own experimental results on the corpus,
achieved with a state-of-the-art LVCSR decoder, measuring the effect of
different feature sets and decoding parameters, and thereby demonstrate that
real-time decoding of our test set is feasible on a desktop PC at 9.2% word
error rate.
