Evaluation of direct speech translation method using inductive learning for conversations in the travelk domain

This paper evaluates a direct speech translation Method with waveforms using the Inductive Learning method for short conversation. The method is able to work without conventional speech recognition and speech synthesis because syntactic expressions are not needed for translation in the proposed method. We focus only on acoustic characteristics of speech waveforms of source and target languages without obtaining character strings from utterances. This speech translation method can be utilized for any language because the system has no processing dependent on an individual character of a specific language. Therefore, we can utilize the speech of a handicapped person who is not able to be treated by conventional speech recognition systems, because we do not need to segment the speech into phonemes, syllables, or words to realize speech translation. Our method is realized by learning translation rules that have acoustic correspondence between two languages inductively. In this paper, we deal with a translation between Japanese and English.