  We present novel methods for assessing the quality of human-translated
aligned texts for learning machine translation models of under-resourced
languages. Malian university students translated French texts, producing either
written or oral translations to Bambara. Our results suggest that similar
quality can be obtained from either written or spoken translations for certain
kinds of texts. They also suggest specific instructions that human translators
should be given in order to improve the quality of their work.
