The BBN Byblos 2000 conversational Mandarin LVCSR system
Han Shu, Chuck Wooters, Owen Kimball, Thomas Colthurst, Fred S. Richardson, Spyros Matsoukas, H. Gish · 2000
This paper describes the year 2000 BBN Byblos Mandarin large vocabulary conversational speech recognition (LVCSR) system, the winning (and only) Mandarin system from the Spring 2 000 Hub-5 evaluation sponsored by NIST. We first outline the training and d ecoding procedures used in the system, and describe the performance of the system used in the e valuation. We then d escribe the e ffect of several features that were not in the e valuation system but have been added since, including Jacobian compensated Vocal Tract Length Normalization (VTLN), system combination, a higher number of system parameters, and additional training data. Together these give a n additional 5.4% relative improvement on character error r ate (CER) from the evaluation system.