Example-based error recovery method for speech translation: repairing sub-trees according to the semantic distance

In speech translation, rec ognition errors produced by the speech rec ognition process can cause parsing and translation errors. Because of this, the development of a r obust error handling framework is quite essential to improve the performance of the speech translation system. Previously, a robust translation method was proposed by Wakita, which translates only reliable parts in utterances. In this method, however, the recall of translated parts for a whole utterance is low, and sometimes no translation is output. In this paper, we propose an example-based error recovery method to solve the low recall problem of Wakita’s method. The proposed method recovers an unreliable utterance, by repairing the parse-tree of the utterance based on similar example parse-trees in the treebank. A recovered translation is generated from the recovered tree.