Bootstrapping a Statistical Speech Translator From a Rule-Based One
DOI:
https://doi.org/10.33011/lilt.v5i.1231Keywords:
translation, speech technology, spoken languageAbstract
We describe a series of experiments in which we start with English to French and English to Japanese versions of a rule-based speech translation system for a medical domain, and bootstrap corresponding statistical systems. Comparative evaluation reveals that the statistical systems are still slightly inferior to the rule-based ones, despite the fact that considerable effort has been invested in tuning both the recognition and translation components; however, a hybrid system is able to deliver a small but significant improvement in performance. In conclusion, we suggest that the hybrid architecture we describe potentially allows construction of limited-domain speech translation systems which combine substantial source-language coverage with high-precision translation.
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This work is licensed under CC BY 4.0, which permits you to use, share, adapt, distribute, and reproduce it in any medium or format, provided you credit the original author(s) and source.