1. A method performed by one or more computers, the method comprising: receiving, from a client device over a computer network, audio data that describes an utterance of a user; accessing, by the one or more computers, stored data of an acoustic model that was generated by: accessing, by a data processing apparatus, speech data that represents utterances of a particular phonetic unit occurring in a particular phonetic context, the speech data comprising values for multiple dimensions; determining, by the data processing apparatus, boundaries for a set of quantiles for each of the multiple dimensions; generating, by the data processing apparatus and for each of the quantiles, a model that models the distribution of values within the quantile; generating, by the data processing apparatus, a multidimensional probability function that indicates, for input speech data representing speech occurring in the particular phonetic context, a probability that the input speech data will have values that correspond to a given set of the quantiles for the multiple dimensions, wherein generating the multidimensional probability function comprises generating an n-gram model wherein the n-grams are sequences of quantile identifiers and the sequences include quantile identifiers for quantiles in at least two dimensions; and storing, by the data processing apparatus, data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function; using, by the one or more computers, the stored data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function to perform speech recognition for an utterance; and providing, to the client device and over the computer network, the transcription for the utterance.
1. A method performed by one or more computers, the method comprising: receiving, from a client device over a computer network, audio data that describes an utterance of a user; accessing, by the one or more computers, stored data of an acoustic model that was generated by: accessing, by a data processing apparatus, speech data that represents utterances of a particular phonetic unit occurring in a particular phonetic context, the speech data comprising values for multiple dimensions; determining, by the data processing apparatus, boundaries for a set of quantiles for each of the multiple dimensions; generating, by the data processing apparatus and for each of the quantiles, a model that models the distribution of values within the quantile; generating, by the data processing apparatus, a multidimensional probability function that indicates, for input speech data representing speech occurring in the particular phonetic context, a probability that the input speech data will have values that correspond to a given set of the quantiles for the multiple dimensions, wherein generating the multidimensional probability function comprises generating an n-gram model wherein the n-grams are sequences of quantile identifiers and the sequences include quantile identifiers for quantiles in at least two dimensions; and storing, by the data processing apparatus, data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function; using, by the one or more computers, the stored data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function to perform speech recognition for an utterance; and providing, to the client device and over the computer network, the transcription for the utterance. 8. The method of claim 1 , further comprising generating other portions of the acoustic model using a plurality of processing nodes, each processing node being assigned different sequences of phonetic units, each of the different processing nodes performing accessing, determining, generating of models, generating of a multi-dimensional probability function, and storing for each of its assigned sequences of phonetic units to generate portions of the acoustic model corresponding to the assigned sequences of phonetic units.