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We introduce Discriminative BLEU (deltaBLEU), a novel metric for intrinsicevaluation of generated text in tasks that admit a diverse range of possibleoutputs. Reference strings are scored for quality by human raters on a scale of[-1, +1] to weight multi-reference BLEU. In tasks involving generation ofconversational responses, deltaBLEU correlates reasonably with human judgmentsand outperforms sentence-level and IBM BLEU in terms of both Spearman's rho andKendall's tau.

deltaBLEU: A Discriminative Metric for Generation Tasks with Intrinsically Diverse Targets