16. A computer-implemented method comprising: as implemented by a server device configured with specific computer-executable instructions, obtaining a first n-gram probability for an n-gram from a first language model; determining, by the server device executing a language model building module, a hash value for the n-gram; obtaining a second n-gram probability from a second language model using the hash value; determining a third n-gram probability using the first n-gram probability and the second n-gram probability; and performing speech recognition using the third n-gram probability.
16. A computer-implemented method comprising: as implemented by a server device configured with specific computer-executable instructions, obtaining a first n-gram probability for an n-gram from a first language model; determining, by the server device executing a language model building module, a hash value for the n-gram; obtaining a second n-gram probability from a second language model using the hash value; determining a third n-gram probability using the first n-gram probability and the second n-gram probability; and performing speech recognition using the third n-gram probability. 20. The computer-implemented method of claim 16 , wherein the first language model is a general purpose language model and the second language model is a specific language model adapted to a user.