The 2009 IBM GALE Mandarin broadcast transcription system
Stephen Mingyu Chu, Daniel Povey, Hong-Kwang Jeff Kuo, Lidia Mangu, Shilei Zhang, Qin Shi, Yong Qin · 2010
This paper gives an up-to-date description of the IBM Mandarin broadcast transcription system developed under the DARPA GALE program. Technical advances over our previous system include a novel acoustic modeling approach using subspace Gaussian mixture models, a speaking rate adaptation method using frame rate normalization, and an effective recipe for lattice combination. We present results on three consortium-defined test sets. It is shown that with these advances, the new system attains a 9% relative reduction in character error rate compared to our previous GALE evaluation system. The reported 9.1% error rate on the phase three evaluation set represents the state of the art in Mandarin broadcast speech transcription.