1. A method for providing response message completion, comprising: determining a response completion model (RCM) using a linear combination of a generic response language model (LM) and a stimulus model with a mixing parameter for a mixing model, the mixing parameter being based, at least in part, on a topic probability, the topic probability to be assigned a value based, at least in part, on a likelihood that a candidate topic is associated with a received stimulus message; receiving a stimulus message (SM); if an incomplete response message includes at least one preceding word, determining at least one candidate next word for the incomplete response message based, at least in part, on the RCM, the SM, and the at least one preceding word and based, at least in part, on estimated word frequencies in stimulus messages from a plurality of stimulus-response message pairs; selecting at least one word from the at least one determined candidate next word; including the selected at least one word within the incomplete response message; and generating a complete response message that is based, at least in part, on the incomplete response message that includes the selected at least one word.
1. A method for providing response message completion, comprising: determining a response completion model (RCM) using a linear combination of a generic response language model (LM) and a stimulus model with a mixing parameter for a mixing model, the mixing parameter being based, at least in part, on a topic probability, the topic probability to be assigned a value based, at least in part, on a likelihood that a candidate topic is associated with a received stimulus message; receiving a stimulus message (SM); if an incomplete response message includes at least one preceding word, determining at least one candidate next word for the incomplete response message based, at least in part, on the RCM, the SM, and the at least one preceding word and based, at least in part, on estimated word frequencies in stimulus messages from a plurality of stimulus-response message pairs; selecting at least one word from the at least one determined candidate next word; including the selected at least one word within the incomplete response message; and generating a complete response message that is based, at least in part, on the incomplete response message that includes the selected at least one word. 3. The method of claim 1 , wherein determining the RCM further comprises: receiving stimulus-response parameters including at least a plurality of stimulus-response message pairs; determining a dictionary containing a plurality of words; determining the LM based, at least in part, on the dictionary and the stimulus-response parameters; determining the stimulus model based, at least in part, on the dictionary and the stimulus response parameters; determining the mixing parameter for the mixing model based, at least in part, on at least the stimulus-response parameters; and determining the RCM based, at least in part, on the LM, the stimulus model, and the mixing parameter.