Despite this inverse relationship, language generation has traditionally received less attention from computational linguists than language understanding, because if the content to be verbalized is available in an unambiguous, formal representation, standard output templates can often be used for generation, at least in sufficiently narrow domains. Even for unrestricted domains, the transduction from an explicit, unambiguous internal semantic representation to a word sequence is much less problematic than reconstruction of an explicit semantic representation from an ambiguous word sequence. A similar asymmetry holds at the level of speech recognition and generation, accounting for the fact that serviceable speech generators (e.g., reading machines for the blind) have been available much longer (since about 1976) than serviceable speech recognizers (appearing around 1999).