A New Two-Layer Approach for Spoken Language Translation

Abstract

The paper proposes a new two-layer approach for spoken language translation. First, we develop translated examples and transform them into speech signals. Second, to retrieve a translated example properly by analyzing speech signals, we expand the translated example into two layers: an intention layer and an object layer. The intention layer is used to examine intention similarity between the speech input and the translated example. The object layer is used to identify the objective components of the examined intention. Experiments were conducted with the languages of Chinese and English. The results revealed that our proposed approach achieves about 86% and 76% understandable translation rate for Chinese-to-English and English-to-Chinese translations, respectively.