8. A method, comprising: receiving, by a first automatic speech recognition component, spoken language in a source language; creating a source language hypothesis from the received spoken language in the source language; translating, with a first machine translation component using a first language model, the source language hypothesis into a target language result; training, with a first training component, the first language model using a source language result, the source language result resulting from translation of a target language hypothesis by a second machine translation component adapted to translate using a second machine translation model, the target language hypothesis created by a second automatic speech recognition component from spoken language in the target language received a human translator; training, with a second training component, the second language model using the target language result; training, with a third training component, the first machine translation model using the target language hypothesis; and training, with a fourth training component, the second machine translation model using the source language hypothesis.
8. A method, comprising: receiving, by a first automatic speech recognition component, spoken language in a source language; creating a source language hypothesis from the received spoken language in the source language; translating, with a first machine translation component using a first language model, the source language hypothesis into a target language result; training, with a first training component, the first language model using a source language result, the source language result resulting from translation of a target language hypothesis by a second machine translation component adapted to translate using a second machine translation model, the target language hypothesis created by a second automatic speech recognition component from spoken language in the target language received a human translator; training, with a second training component, the second language model using the target language result; training, with a third training component, the first machine translation model using the target language hypothesis; and training, with a fourth training component, the second machine translation model using the source language hypothesis. 10. The method of claim 8 , further comprising: recognizing, by a universal speech recognition component, spoken language in any language; and enhancing, by the universal speech recognition component, a target language hypothesis that has been created from a monolingual extract of text material in the target language.