In this paper, we report on the automatic recognition of Japanese broadcast-news speech. We have been working on large-vocabulary continuous speech recognition (LVCSR) for Japanese newspaper speech transcription and have achieved good performance. We have recently applied our LVCSR system to transcribing Japanese broadcast-news speech. We extended the vocabulary from 7k words to 20k words and trained the language models using newspaper texts and broadcast-news manuscripts. These two language models were applied to our evaluation speech sets. The language model trained using broadcast-news manuscripts achieved better results for broadcast-news speech than the language model trained using newspaper texts, which achieved better results for newspaper speech. We achieved a word error rate of 19.7% for anchor-speaker's speech by using a bigram language model and a trigram language model both trained using broadcast-news manuscripts.