The need for translation among the world’s thousands of natural languages makes information access and communication costly. One possible solution is lemmatic communication: A human sender encodes a message into sequences of lemmata (dictionary words), a massively multilingual lexical translation engine translates them into lemma sequences in a target language, and a human receiver interprets them to infer the sender’s intended meanings. Using a 13million-lemma, 1300-language translation engine, we conducted an experiment in lemmatic communication with Spanish- and Hungarian-speaking subjects. Translingual communication was less successful than intralingual communication, and intralingual communication was less successful when the lemma sequences were artificially randomized before the receiver saw them (simulating word-order differences among languages). In all conditions, however, meanings were transmitted with high or moderate fidelity in at least 40 % of the cases. The results suggest interface and translation-algorithm improvements that could increase the efficacy of lemmatic communication.