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. 20. The computer storage media of claim 17 , wherein individual multi-reference responses in the set of multi-reference responses includes a rating, and wherein the response assessment engine, when executed, further causes at least one processor to: normalize the rating to form a normalized rating within a range from negative one to positive one, wherein a negative value rating indicates that a multi-reference response in the set of multi-reference responses is sub-optimal.