10. A computer-implemented method comprising: receiving, by a term pre-processor module of a server-based automated speech recognition system that includes (a) the term pre-processor module, (b) a vocabulary generator module, (c) a language model biaser module, and (d) an automated speech recognizer, and from a device associated with a target user, (i) data including a set of terms associated with the target user that includes terms from one or more queries previously submitted by the target user, and, (ii) from each of multiple other users, data including a set of terms associated with the other user; selecting, by the vocabulary generator module of the server-based automated speech recognition system, a particular term from the set of terms associated with the target user; identifying, by the vocabulary generator module of the server-based automated speech recognition system, a particular other term, from among the sets of terms that are associated with the multiple other users, that is indicated as related to the particular term; obtaining, by the language model biaser module of the server-based automated speech recognition system and based on the particular other term, from among the sets of terms that are associated with the multiple other users, that is indicated as related to the particular term, a biased language model; using, by the automated speech recognizer of the server-based automated speech recognition system, the biased language model generate a speech recognition output; and providing, by the server-based automated speech recognition system, the speech recognition output to the device associated with the target user.
10. A computer-implemented method comprising: receiving, by a term pre-processor module of a server-based automated speech recognition system that includes (a) the term pre-processor module, (b) a vocabulary generator module, (c) a language model biaser module, and (d) an automated speech recognizer, and from a device associated with a target user, (i) data including a set of terms associated with the target user that includes terms from one or more queries previously submitted by the target user, and, (ii) from each of multiple other users, data including a set of terms associated with the other user; selecting, by the vocabulary generator module of the server-based automated speech recognition system, a particular term from the set of terms associated with the target user; identifying, by the vocabulary generator module of the server-based automated speech recognition system, a particular other term, from among the sets of terms that are associated with the multiple other users, that is indicated as related to the particular term; obtaining, by the language model biaser module of the server-based automated speech recognition system and based on the particular other term, from among the sets of terms that are associated with the multiple other users, that is indicated as related to the particular term, a biased language model; using, by the automated speech recognizer of the server-based automated speech recognition system, the biased language model generate a speech recognition output; and providing, by the server-based automated speech recognition system, the speech recognition output to the device associated with the target user. 11. The method of claim 10 , wherein, for each user, the set of terms associated with the user includes terms that are indicated as terms that have been accepted by the user.