1. A method of automatic speech recognition, comprising the steps of: a) receiving a text message at a speech recognition client device; b) processing the text message with conversational context-specific language models and emotional context-specific language models stored on the client device using at least one processor of the client device to identify a conversational context and an emotional context corresponding to the text message; c) synthesizing speech from the text message; d) communicating the synthesized speech via a loudspeaker of the client device to a user of the client device; e) receiving a reply utterance in response to the text message from the user via a microphone of the client device that converts the reply utterance into a speech signal; f) pre-processing the speech signal using the at least one processor to extract acoustic data from the received speech signal; g) communicating the extracted acoustic data, the identified conversational context, and identified emotional context to a speech recognition server; h) identifying an acoustic model of a plurality of acoustic models stored at the server to be used for decoding the acoustic data based on the identified conversational context, the identified emotional context, or both; i) decoding the acoustic data using the identified acoustic model to produce a plurality of hypotheses for the reply utterance; and j) post-processing the plurality of hypotheses to identify one of the hypotheses as the reply utterance; k) presenting the identified hypothesis to the user; l) seeking confirmation from the user that the identified hypothesis is correct; m) outputting the identified hypothesis as at least part of a reply text message if the user confirms that the identified hypothesis is correct; otherwise n) using the emotional context to improve identification of the acoustic model, and repeating steps e) through m).