Developing high performance asr in the IBM multilingual speech-to-speech translation system

This paper presents our recent development of the real-time speech recognition component in the IBM English/Iraqi Arabic speech-to-speech translation system for the DARPA Transtac project. We describe the details of the acoustic and language modeling that lead to high recognition accuracy and noise robustness and give the performance of the system on the evaluation sets of spontaneous conversational speech. We also introduce the streaming decoding structure and several speedup techniques that achieves best recognition accuracy at about 0.3 x RT recognition speed.