In this paper, we present advanced techniques that improved the performance of IBM Malay-English speech translation system significantly. During this work, we generated linguistics-driven hierarchical rules to enhance the formal syntax-based translation model; designed an active learning approach with bi-directional translations that outperformed unsupervised training; utilized translation direction information in parallel training corpus to build direction-specific interpolated language models for machine translation. There is 20% relative improvement achieved in the translation performance through all these techniques. A state-of-the-art Malay speech recognition system was also established as one of the crucial modules in the rapidly developed Malay-English speech translation.
['Bing Xiang', 'Bowen Zhou', 'Martin Cmejrek']
Advances in syntax-based Malay-English speech translation