7. At least one computer-readable medium encoded with instructions that, when executed by at least one computer system, perform a method for speech recognition of input speech in a language from a non-native speaker, the method comprising acts of: generating, based upon a first-language acoustic model, a first-language phoneme sequence from one or more feature vectors, the one or more feature vectors being based upon one or more voice-induced electrical signals that result from the input speech, wherein the first-language acoustic model corresponds to a first language; determining a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model, wherein the second-language lexicon model corresponds to a second language that is different from the first language; determining a confidence score associated with a combination of the first-language acoustic model and the second-language lexicon model; and selecting the first-language acoustic model from a plurality of acoustic models based at least in part on the determined confidence score, each of the plurality of acoustic models corresponding to a different respective language.
7. At least one computer-readable medium encoded with instructions that, when executed by at least one computer system, perform a method for speech recognition of input speech in a language from a non-native speaker, the method comprising acts of: generating, based upon a first-language acoustic model, a first-language phoneme sequence from one or more feature vectors, the one or more feature vectors being based upon one or more voice-induced electrical signals that result from the input speech, wherein the first-language acoustic model corresponds to a first language; determining a second-language speech segment from the first-language phoneme sequence based upon a second-language lexicon model, wherein the second-language lexicon model corresponds to a second language that is different from the first language; determining a confidence score associated with a combination of the first-language acoustic model and the second-language lexicon model; and selecting the first-language acoustic model from a plurality of acoustic models based at least in part on the determined confidence score, each of the plurality of acoustic models corresponding to a different respective language. 8. The at least one computer-readable medium of claim 7 , wherein the act of selecting the first-language acoustic model from the plurality of acoustic models comprises selecting the first-language acoustic model based at least in part of the determined confidence score being greater than another confidence score associated with a combination of another first-language acoustic model and the second-language lexicon model.