17. One or more computer storage media embodying computer-executable components, said components comprising: an extraction component that when executed causes at least one processor to: extract a plurality of candidate context-message-response n-tuples from at least one source of conversational data; and select at least one candidate context-message-response n-tuple from the plurality of candidate context-message-response n-tuples associated with a machine-generated response to form a set of multi-reference responses; and a response assessment engine that when executed causes at least one processor to: generate a metric score for the machine-generated response based on the set of multi-reference responses, a conversational context of the machine-generated response, and an assessment metric, the metric score indicating a quality of the machine-generated response relative to the set of multi-reference responses.
17. One or more computer storage media embodying computer-executable components, said components comprising: an extraction component that when executed causes at least one processor to: extract a plurality of candidate context-message-response n-tuples from at least one source of conversational data; and select at least one candidate context-message-response n-tuple from the plurality of candidate context-message-response n-tuples associated with a machine-generated response to form a set of multi-reference responses; and a response assessment engine that when executed causes at least one processor to: generate a metric score for the machine-generated response based on the set of multi-reference responses, a conversational context of the machine-generated response, and an assessment metric, the metric score indicating a quality of the machine-generated response relative to the set of multi-reference responses. 19. The computer storage media of claim 17 , wherein the response assessment engine, when executed, further causes at least one processor to: select a response from the plurality of candidate context-message-response n-tuples based on the conversational context of the response to form a reference response in the set of multi-reference responses, wherein the conversational context associated with the reference response corresponds to the conversational context of the machine-generated response, wherein the conversational context comprises linguistic context data and non-linguistic context data, wherein the linguistic context data comprises message-response data pairs preceding the selected message and the machine-generated response in a conversation.